It is known that noise immunity and secrecy are the two most important components of the noise immunity of the SRS.

At the same time, in general case the noise immunity of the SRS with frequency hopping (however, like any other SRS) is understood as the ability to function normally, performing the tasks of transmitting and receiving information in the presence of radio interference. Therefore, the noise immunity of the SRS is the ability to withstand the harmful effects of various types of radio interference, including, first of all, organized interference.

The strategy for combating organized interference of the SRS with frequency hopping consists, as a rule, in the "avoidance" of the SRS signals from the effects of interference, and not in the "confrontation" with them, as is implemented in the SRS with FM1IPS. Therefore, in SRS with frequency hopping, an important characteristic in protection against interference is the actual time of operation at one frequency. The shorter this time, the higher the probability that SRS signals with frequency hopping will not be affected by organized interference.

The noise immunity of the SRS with frequency hopping depends not only on the operating time at one frequency, but also on others important parameters interference stations (SP) and SRS, for example, on the type of interference and its power, the power of the useful signal, the structure of the receiving device and the methods of noise immunity incorporated in the SRS.

An effective effect of interference on the SRS with frequency hopping can only be achieved if the jammer knows the relevant parameters of the SRS signals, for example, channel center frequencies, frequency hopping rates, information bandwidth, signal strength and interference at the location of the SRS receiver. Specified parameters The jammer obtains the SRS, as a rule, directly with the help of an electronic intelligence station (RTR), as well as by converting the measured parameters of the SRS into other characteristics of the SRS that are functionally related to them. For example, by measuring the duration of a frequency hop, one can calculate the bandwidth frequency channel SRS receiver.

In the general case, RTR, by receiving and analyzing intercepted signals not only from the SRS, but also from other radio-electronic means (RES), provides the collection of information about the opposing party as a whole. The SRS and RES signals contain many technical characteristics that are intelligence information. These characteristics define the "electronic handwriting" of the SRS and RES and allow you to establish their capabilities, purpose and belonging.

A generalized algorithm for collecting data by electronic intelligence on signal parameters and characteristics of the SRS is shown in Fig. 1.18.

To assess the noise immunity of the SRS under the influence of various kinds interference must have appropriate indicators. With the selected models of the signal, the inherent noise of the receiver and additive interference in discrete message transmission systems, the preferred indicator of a quantitative measure of noise immunity is the average probability of error (MEP) per bit of information .

Other indicators of the noise immunity of the SRS, for example, the required signal-to-noise ratio, which ensures a given quality of information reception, the probability of an error in code word and others, can be expressed in terms of CBO per bit. Minimization of SVR per bit under the condition of equiprobable transmission of symbols can be achieved by using an algorithm that implements the maximum likelihood rule

With all

which for binary SRS has the form:

where is the likelihood ratio for the th signal.

In the further presentation, the greatest attention will be focused on the development and analysis of algorithms for calculating SVR per bit of information. The analysis of CBO per bit will be carried out under the action of Gaussian noise of the CPC receiver and additive organized interference, mainly in relation to canonical (typical) FM systems, which are basic foundation more complex SRS.

Noise immunity of radio communication systems with the expansion of the spectrum of signals by the method of pseudo-random tuning operating frequency. IN AND. Borisov, V.M. Zinchuk, A.E. Limarev, N.P. Mukhin, V.I. Shestopalov. / 2000

UDC 621.391.372.019 Noise immunity of radio communication systems with the expansion of the spectrum of signals by the method of pseudo-random tuning of the operating frequency. IN AND. Borisov, V.M. Zinchuk, A.E. Limarev, N.P. Mukhin, V.I. Shestopalov. - M.: Radio and communication, 2000. - 384 p.: ill. ISBN-5-256-01392-0 The main principles and characteristics of the signal spectrum spreading method due to pseudo-random frequency tuning (PRFC) are outlined. Analysis possible ways Improving the noise immunity of typical radio communication systems (SRS) with frequency hopping and frequency shifting in the conditions of organized interference and self-noise of the SRS. The problems of synthesizing and analyzing the noise immunity of adaptive signal demodulation algorithms with frequency hopping and frequency separation of information symbols are solved under conditions of a priori uncertainty about the power of the noise concentrated over the spectrum. Typical block diagrams and algorithms for the operation of the main devices of the synchronization subsystem in the SRS with frequency hopping, indicators and methods for assessing the effectiveness of cyclic search procedures. The joint use of signals with frequency hopping and adaptive antenna arrays(AAR). An adaptation algorithm is analyzed that provides the maximum signal-to-noise ratio. The algorithms and operating characteristics of energy detectors that provide detection of signals with frequency hopping for the purpose of their electronic suppression are described. For scientists, engineers, graduate students and senior students specializing in the field of research and development of radio communication systems.

Il.211. Table 14. Bibliography 112 titles

Reviewers:
doctor of tech. Sciences, Professor Yu.G. Bugrov
doctor of tech. Sciences, Professor Yu.G. Sosulin
doctor of tech. Sciences, Professor N.I. Smirnov

Foreword

The most important way to achieve the required noise immunity of radio communication systems (RSS) under the influence of organized (deliberate) interference is the use of signals with pseudo-random frequency hopping (PRFC) and the use of optimal and quasi-optimal algorithms for processing such signals.

A large number of works by domestic and foreign authors are devoted to the problem of noise immunity of SRS with the expansion of the spectrum of signals by the frequency hopping method. These, first of all, should include the well-known monographs and works of the scientific schools of L.E. Varakina and G.I. Tuzov; unpublished until now in Russian books by D.J. Torrieri "Principles of Secure Communication Systems", Dedham, MA.: Artech House, Inc., 1985; M.K. Simon, J.K. Omura, R.A. Scholtz, B.K. Levitt "Spread Spectrum Communication", vol. I-III, Rockville, MD.: Computer Science Press, 1985. In 1998, the publishing house "Artech House, Inc.", specializing in the field of radar, radio communications, electronic jamming, etc., published books D.C. Schleher "Advanced Electronic Warfare Principles", E. Waltz "Introduction to Information Warfare". The Association of American Communication Theorists and Technologists under the direction of Professor J.S. Lee (Inc. 2001, Jefferson Davis Highway, Suite 601. Arlington, Virginia 22202) has published more than ten papers, including commissioned papers, on various aspects of the noise immunity of SRS with frequency hopping. In 1999, the publishing house "Radio and Communication" published a monograph by V.I. Borisov, V.M. Zinchuk "Noise immunity of radio communication systems. Probabilistic-temporal approach".

However, the problem of the effectiveness of SRS with frequency hopping, research and development promising ways Improving the noise immunity of the SRS, especially in the context of constant improvement of the tactics and techniques of electronic countermeasures (REW), remain relevant and important both from a scientific and practical point of view.

Appeared in recent times the possibility of wide introduction in the SRS of high-speed microprocessor technology and modern element base make it possible to implement new principles for the formation, reception and processing of signals with frequency hopping, including frequency diversity of symbols with a high multiplicity and short duration of elements, the sharing of M-ary frequency shift keying(FM) and error-correcting coding, signals with frequency hopping and adaptive antenna arrays, etc. All this makes it possible to ensure high noise immunity of the SRS when exposed to various types of organized interference.

The topics discussed in the book, their content and presentation reflect to a certain extent state of the art the main aspects of the problem of interference immunity of the SRS, including, among other things, the issues of synchronization, the joint use in the SRS of signals with frequency hopping and adaptive antenna arrays, as well as the detection of signals with hopping frequency by electronic intelligence stations that ensure the effective functioning of EW systems. The content of the book is subject to a single goal - the analysis of the effectiveness of possible ways to increase the noise immunity of the SRS with frequency hopping in the conditions of REB.

The book is based on own works authors, it widely uses the results of research by domestic and foreign experts. At the same time, the authors, referring to some issues of noise immunity of the SRS with frequency hopping to the works of foreign specialists unpublished in Russian, presented a number of book materials in the form of analytical reviews.

The book uses a mathematical apparatus available to engineers, provides structural diagrams of typical SRS, graphs and tables illustrating the possibilities of methods of noise immunity of SRS with frequency hopping. The desire to simplify the material presented led to the fact that the book mainly deals with typical binary SRS with FM, and communication channels - without attenuation and with Gaussian noise.

Reading the book assumes knowledge of the foundations of the statistical theory of communication, set forth in the most famous, now classic, monographs by V.I. Tikhonov "Statistical radio engineering", - M .: Radio and communication, 1982, and B.R. Levin" Theoretical basis statistical radio engineering", - M.: Radio and communication, 1989.

For great help in working on foreign literature, the authors are grateful to the translators Zykov N.A., Luneva S.A., Titova L.S.

The authors are grateful to Yu.G. Belous, E.I. Goncharova, T.V. Dorovskikh, E.V. Izhbakhtina, T.F. Kapaeva, N.A. Parfenova, E.V. Pogosova, O.I. Sorokina and N.N. Starukhina for computer set materials of the book, carrying out numerous calculations, development and preparation of graphic and illustrative material.

FOREWORD		8
INTRODUCTION		10
Chapter 1.
RADIO COMMUNICATION SYSTEMS WITH SIGNAL SPECTRUM EXPANSION BY THE METHOD OF PSEUDO-RANDOM FREQUENCY HANDLING: GENERAL PRINCIPLES		13
1.1.	Brief description of signal spectrum spreading by frequency hopping	13
1.1.1.	Basic principles and methods of signal spectrum spreading	13
1.1.2.	Method of pseudo-random tuning of the operating frequency	19
1.1.3.	Typical block diagrams of radio communication systems with frequency hopping	24
1.2.	Signal spreading factor and noise margin of a radio communication system with frequency hopping	36
1.3.	General characteristic of noise immunity of radio communication systems with frequency hopping	42
1.3.1.	Noise immunity of radio communication systems with frequency hopping	42
1.3.2.	Stealth of signals of radio communication systems with frequency hopping	44
1.3.3.	Radio-electronic conflict: "radio communication system - REP system"	53
1.4.	Models and a brief description of main types of interference	56
Chapter 2
NOISE IMMUNITY OF TYPICAL RADIO COMMUNICATION SYSTEMS WITH FRCH AND FREQUENCY KEYPAD		64
2.1.	Conditional bit error probability for binary FM	64
2.2.	Evaluation of the impact of noise interference in a part of the band on radiocommunication systems with frequency hopping and non-random FM	73
2.3.	Evaluation of the impact of noise interference in a part of the band on radiocommunication systems with frequency hopping and random binary FM	80
2.4.	Evaluation of the impact of response interference on radio communication systems with frequency hopping and FM	86
2.4.1.	Estimation of the time capabilities of the station of response interference	86
2.4.2.	Evaluation of the impact of response noise interference on radio communication systems with frequency hopping and FM	96
2.4.3.	Evaluation of the impact of response harmonic interference on radio communication systems with frequency hopping and FM	102
2.5.	Noise immunity of radio communication systems with frequency hopping, binary FM and block coding	111
Chapter 3
SYNTHESIS AND ANALYSIS OF THE EFFICIENCY OF ADAPTIVE ALGORITHMS FOR DIFFERENTIATION OF SIGNALS WITH FREQUENCY KEYPAD, FREQUENCY KEYPAD, AND SYMBOL FREQUENCY DISTRIBUTION		124
3.1.	Synthesis of the optimal adaptive algorithm for distinguishing signals with intra-symbol frequency hopping and FM	124
3.2.	Quasioptimal Adaptive Algorithm for Distinguishing Signals with Intrasymbol Frequency Hopping and Binary FM	132
3.3.	Estimation of Noise Immunity of the Synthesized Adaptive Algorithm for Distinguishing Signals with Intrasymbol Frequency Hopping and Binary FM	141
3.3.1.	The case of "weak" signals	142
3.3.2.	The case of "strong" signals	148
Chapter 4
NOISE IMMUNITY OF ADAPTIVE SIGNAL DEMODULATION ALGORITHMS WITH INTRA-BIT hop hopping and binary frequency shift keying		152
4.1.	Structural diagrams of demodulators	152
4.2.	Linear Addition Demodulator Noise Immunity	157
4.3.	Noise immunity of a demodulator with non-linear summation of samples	164
4.4.	Noise immunity of the soft-limiter demodulator	170
4.5.	Noise immunity of a self-normalizing demodulator	173
4.6.	Influence of adaptive gain control on the noise immunity of the CRS	182
4.7.	Comparative Analysis of the Noise Immunity of Signal Demodulators with Intra-Bit Frequency Frequency and Binary FM	189
Chapter 5
NOISE IMMUNITY OF RADIO COMMUNICATION SYSTEMS WITH FRCH WITH THE JOINT APPLICATION OF FREQUENCY KEYPULATION, SYMBOL FREQUENCY DISTRIBUTION AND BLOCK CODING		194
5.1.	Noise immunity of radio communication systems with frequency hopping at M-ary FM and L-fold spacing of symbols in frequency	194
5.1.1.	Conditional error probability per bit of information	197
5.1.2.		199
5.2.	Noise immunity of radio communication systems with frequency hopping, M-ary FM, block coding and L-fold frequency spacing of code words	203
5.2.1.	Block diagram of a radio communication system.	203
5.2.2.	Average probability of error per bit of information.	206
5.2.3.	Analysis of the average probability of error per bit of information	209
Chapter 6
SYNCHRONIZATION IN RADIO COMMUNICATION SYSTEMS WITH PSEUDO-RANDOM FREQUENCY RESTRICTION		214
6.1.	The purpose of the synchronization subsystem.	214
6.2.	Descriptive model of the synchronization subsystem.	219
6.2.1.	Typical block diagram of the synchronization subsystem	219
6.2.2.	Typical block diagrams and algorithms for the functioning of the main devices of the synchronization subsystem	221
6.3.	Indicators and evaluation of the effectiveness of cyclic search procedures.	230
Annex A.6.1. Upper bound on average normalized search time		242
Annex P.6.2. Upper bound on the probability of correct detection		243
Chapter 7
ADAPTIVE ANTENNA ARRAYS IN RADIO COMMUNICATION SYSTEMS WITH PSEUDORANDOM FREQUENCY TUNING		244
7.1.	Influence of signals with frequency hopping on the characteristics of an adaptive antenna array	244
7.2.	Maximin Signal and Noise Processing Algorithm	256
7.3.	Implementation and capabilities of the maximin algorithm	259
7.4.	Modernization of the maximin algorithm	271
7.4.1.	Parametric processing.	272
7.4.2.	Spectral processing	274
7.4.3.	Proactive processing.	277
Chapter 8
DETECTION OF SIGNALS WITH PSEUDONANDOM FREQUENCY AGGREGATION		281
8.1.	Detection of signals of unknown structure.	281
8.2.	Broadband Energy Detector	286
8.3.	Multi-channel energy detectors	292
8.3.1.	Quasi-optimal multi-channel detector	293
8.3.2.	Multichannel adder-type detector with filter block	295
8.3.3.	Model of an adder-type detector with a filter block when intercepting signals with a slow frequency hop	297
8.3.4.	Multichannel adder-type detector with a filter block in the band part.	305
8.3.5.	The mismatch in time and frequency between the characteristics of the signal with frequency hopping and the parameters of the detector.	309
8.3.5.1.	Time Mismatch	310
8.3.5.2.	Frequency Mismatch	311
8.4.	Multichannel adaptive energy detector under the influence of interfering signals	313
8.4.1.	Structural diagram of a multichannel adaptive energy detector with threshold level adjustment	313
8.4.2.	False alarm probability and adaptive threshold adjustment	316
8.4.3.	Probability of detection.	320
8.4.4.	Influence of time mismatch on signal detection.	323
8.5.	Other possible types signal detectors with frequency hopping	331
8.5.1.	Correlation radiometer.	331
8.5.2.	Digital spectrum analyzer.	332
8.5.3.	The method of opening the frequency-time matrix of a signal with frequency hopping	334
Annex A.8.1. Algorithms for computing the generalized Marcum Q-function.		335
Clause 8.1.1. Formulation of the problem		335
Clause 8.1.2. Representation by power series.		339
Clause 8.1.3. Representation in the form of Neumann series.		341
Clause 8.1.4. Numerical Integration		345
Clause 8.1.5. Gaussian approximation		349
Clause 8.1.6. Numerical results		350
Annex A.8.2. Analysis of probabilistic-temporal characteristics of signal detection algorithms		353
Clause 8.2.1. Probabilistic-temporal characteristics of the main types of detectors		353
Clause 8.2.2. Algorithms for calculating the probabilistic-temporal characteristics of the main types of detectors		356
Clause 8.2.2.1. Deterministic Signal Detector		356
Clause 8.2.2.2. Random Phase Quasi-Deterministic Signal Detector		359
A.8.2.2.3 Signal detector of unknown structure.		360
Clause 8.2.2.4. Detectors with constant false alarm rate		363
A.8.2.3 Numerical results		367
LIST OF MAIN ABBREVIATIONS		372
BASIC SYMBOLS		374
BIBLIOGRAPHY		377

The owners of the patent RU 2439794:

The invention relates to the field of radio communications and can be used to provide radio communications in the presence a large number interference of various nature. Technical result- increasing the noise immunity and mobility of the communication system. The device contains M (M≥2) radio stations, each of which contains N (N≥1) diversity antennas connected to the first inputs of the respective receiving paths, N analog-to-digital converters, a radio modem with a connected transceiver antenna, a multiplexer, a demultiplexer, an adaptive noise canceller , reference generator and control unit. 4 ill.

The invention relates to the field of radio communications and can be used to provide radio communications in the presence of a large number of interference of various nature.

A radio communication system is known, in radio stations (PC) of which adaptive interference cancellers (ACC) are used, given, for example, in the description of utility model No. 30044 "Adaptive interference canceller", 2002.

The disadvantage of this automatic transmission is the low efficiency when the communication system operates in a complex interference environment with more than one interference.

The closest in technical essence is a radio communication system, the radio station of which uses a multi-channel adaptive interference canceller, described in the book "Adaptive interference compensation in communication channels" / Ed. Yu.I.Loseva, M., Radio and communication, 1988, p.22, taken as a prototype.

Block diagram of the prototype system, consisting of N radio stations, is shown in Fig.1.

Scheme of the receiving part of the prototype radio station is shown in figure 2, where it is indicated:

1 - N - spaced antenna elements;

2 - N - receiving paths;

3 - control unit;

4 - reference generator;

6 - N-channel adaptive interference canceller (ACC).

The receiving part of the prototype radio station contains N diversity antennas 1 connected to the first inputs of the corresponding N receiving paths 2. The output of the common reference oscillator 4 is connected to the second inputs of the corresponding N receiving channels 2, line outputs which through the corresponding N analog-to-digital converters 5 are connected to the corresponding inputs of the N-channel automatic transmission 6, the output of which is the output of the useful signal. The output of the control unit 3 is connected to the third inputs of the receiving paths 2.

The prototype device works as follows.

The useful signal and interference coming from different directions are received simultaneously by all antennas 1. From the outputs of the receiving antennas, the mixture of signal and interference is fed to the inputs of the corresponding receiving paths 2, where frequency selection is performed, the input waveform is converted to an intermediate frequency and the necessary linear amplification. For coherent reception of signals by N diversity antennas 1, a common reference oscillator 4 is used. The control unit 3 generates signals that control the tuning frequency and other parameters of all receiving paths simultaneously.

Signal and noise mixtures from the output of each receiving path are converted into N analog-to-digital converters 5 into digital samples and fed to the input of the N-channel interference canceller 6. At the output of the automatic transmission 6, samples of the useful signal are formed, cleared of interference for further processing in the radio station: demodulation , decoding, etc.

On the one hand, the need for simultaneous suppression of a large (more than one) number of interferences occurs quite rarely. And therefore, the large dimensions and weight of the PC, due to the presence of a multi-channel receiver and a multi-element antenna system, are in most cases redundant. On the other hand, in the case of, for example, military radio communications, even a short interruption of communication due to interference entails extremely heavy losses. Hence, there is a need for a compromise, which consists in increasing the number of compensation channels for receiving the ACP only as interference effects appear, that is, the need to dynamically change the configuration of the PC receiving device depending on the interference environment. And this is possible with sharing receiving channels and antennas are located close (at a distance of several wavelengths) of the same type of PC, for example, a communication center.

disadvantage known system communication is the cumbersome implementation in radio stations of a multi-channel receiver and a multi-element antenna system. This shortcoming is decisive in the case, for example, mobile means connections.

The task of the proposed technical solution is to increase the noise immunity and mobility of the communication system.

To solve the problem in a radio communication system consisting of M (M≥2) radio stations, each of which contains N (N≥1) diversity antennas connected to the first inputs of the respective receiving paths, the linear outputs of which are connected through the corresponding N analog-to-digital converters to the corresponding N inputs of the adaptive noise canceller, as well as the reference generator, the output of which is connected to the second inputs of the N receiving paths, and the control unit connected to the third inputs of the receiving paths, according to the invention, a radio modem with a connected transceiver antenna is introduced into the receiving part of each radio station of the system, as well as a multiplexer and a demultiplexer, moreover, the outputs of N analog-to-digital converters are connected to the corresponding inputs of the multiplexer, the output of which is connected to the information input of the radio modem, the information output of which is connected to the inputs of the control unit and the demultiplexer, the outputs of which are connected to the corresponding inputs K input odes of the adaptive noise canceller, while the control inputs of the multiplexer, demultiplexer and radio modem are connected to the corresponding outputs of the control unit.

The diagram of the receiving part of the PC, included in the proposed radio communication system, is shown in figure 3, where it is indicated:

1.1-1.N - spaced antenna elements;

2.1-2.N - receiving paths;

3 - control unit;

4 - reference generator;

5.1-5.N - analog-to-digital converters (ADC);

6 - N-channel analog noise canceller (ACC);

7 - multiplexer;

8 - demultiplexer;

9 - radio modem;

10 - transceiver antenna of the radio modem.

The proposed device contains N receiving antennas 1 connected to the first inputs of the corresponding N receiving paths 2, the outputs of which are connected to the inputs of the corresponding N ADC 5, the outputs of which are connected to the corresponding N inputs of the automatic transmission 6, the output of which is the output of the useful signal. In this case, the output of the reference oscillator 4 is connected to the second inputs N of the receiving paths 2. In addition, the outputs N of the ADC 5 are connected to the corresponding inputs of the multiplexer 7, the output of which is connected to the information input of the radio modem 9 with a transceiver antenna 10 connected to its other input, the information output of the radio modem 9 is connected to the inputs of the demultiplexer 8 and the control unit 3. Moreover, the K outputs of the demultiplexer 8 are connected to the K inputs of the automatic transmission 6, respectively. The first output of the control unit 3 is connected to the second inputs of the receiving paths 2. The control inputs of the multiplexer 7, demultiplexer 8 and radio modem 9 are connected to the corresponding outputs of the control unit 3.

Each radio station with a minimum number of antennas N (hence, minimum dimensions), for example, two, has a built-in automatic transmission with (N + K) inputs, which allows compensating for (N + K-1) interference. Of these, N inputs are provided by their own antennas, and K additional inputs are provided by antennas of neighboring PCs, whose digitized signals are transmitted using built-in radio modems. With simultaneous exposure to more than one interference, a two-channel compensator does not allow you to select a useful signal.

In this case, in the proposed communication system, a PC serving a subscriber with a high priority has the ability to increase the number of suppressed interference without increasing its size by using additional antennas and receiving paths located in other radio stations of the communication center.

To provide this possibility, a radio modem with a transceiver antenna was additionally introduced into each PC, operating in another frequency range. It provides, first, external management over a radio channel from a higher priority subscriber by the operating mode (tuning frequency, etc.) of individual radio paths in the PC. Secondly, through the radio modem are transmitted (or received) digital values samples of signals from the output of linear radio paths of neighboring PCs.

The proposed communication system works as follows.

Each PC can operate in the system either as a master (with high priority) or as a slave (with low priority).

In the first case (with high priority), the PC works as follows.

Initial organization local network no built-in radios required external commands and provided by their internal software as soon as they are within range of each other. At the same time, the radio modems automatically exchange technological data, in particular, about the value of the system time, mutual priorities, etc. This is implemented in most well-known built-in radio modems, such as Bluetooth, ZigBee, etc.

Further, the control unit 3 of the master PC through its radio modem transmits commands to the slave PCs to tune these PCs to the same frequency, and then initiates the transmission of digital samples of the received signals through their built-in radio modems.

The digitized signals of the slave PCs received via the radio modem channel, after demodulation, are fed to the demultiplexer 8 and the input of the control unit 3. Depending on individual number of the slave PC and the number of its antenna in the local network, the control unit addresses the signal samples of this PC to the same outputs of the demultiplexer 8. Thus, N inputs of the automatic transmission receive signals from their own radio paths, and K other inputs receive samples K of the slave PCs. As a result, the amount of suppressed interference increases to (N+K-1) without increasing the dimensions of the PC.

In the second case (with low priority), the PC works as follows.

After initial organization of the local network of radio modems, the slave PC receives the configuration control commands through its radio modem (they are received by the PC control unit), and then the control unit 3 sends sequentially through the multiplexer 7 the samples of the signals of N receiving channels to the information input of the radio modem 9. The samples of the radio path signals are transmitted in the form of packets to the master PC.

Figure 4 shows the timing diagram of the signals (packets) received by the master radio station via the radio modem channel 9. At the time T=0 in the master radio station itself (in the ADC 5), signal samples are taken from the output of their own receiving paths 2.

The duration of a frame in which data is periodically transmitted from other PCs should not exceed the duration of the sampling interval T d =1/F d, where F d is the sampling frequency of the received signal. She, as you know, must be at least, twice the upper frequency in the signal spectrum. Thus, until the end of the interval T d in the leading PC there are samples of the signal received by neighboring PCs at the same time.

Due to the presence in the local network system clock, signal counts in all spaced radio paths are made simultaneously. Batch mode The transmission of samples allows then to combine at the input of the automatic transmission 6 of the master PC the signal samples taken at the same moment in the spaced slave PCs.

Spatial diversity reception, carried out with the help of receiving radio paths of other objects connected via a local network, will be called network reception.

Thus, under conditions of network reception, all antennas connected to their PC radio paths located at the communication center are shared resource, which can be quickly redistributed using a local network formed by radio modems built into the PC, depending on the number and priority of subscribers served and the changing interference environment.

Such a construction of the communication system provides, in the most extreme case, under the influence of a complex of interference, the pooling of the resources of all PCs available at the communication center to ensure stable communication with the highest priority official.

In addition, the proposed communication system provides a significant increase in the reliability of radio communications by providing technical feasibility anyone official(in case of operational necessity or in case of failure of one's PC) use any operable PC of neighboring objects covered by a local communication and control network.

In a particular case, each PC of the system may have one antenna and one receive path (N=1). Such a PC lacks interference suppression capability. However, due to the presence of an automatic transmission with (K + 1) inputs in it, it becomes possible to provide suppression of K interference if there is a K PC in the local area network.

The described pooling of resources for the purpose of noise immunity of the most critical communication lines is possible not only when organizing a communication center, but in any case when PCs are within the reach of built-in radio modems. For example, when moving individual PCs to vehicles in a column, when closely spaced PCs can be connected via a local network.

Noise immunity SHPSS

Understanding Broadband Signals

1.1 Definition of NPS. The use of SHPS in communication systems

Broadband (complex, noise-like) signals (BSS) are those signals in which the products of the active spectrum width F and the duration T are much greater than unity. This product is called the signal base B. For NPS

B = FT>>1 (1)

Broadband signals sometimes called complex as opposed to simple signals(for example, rectangular, triangular, etc.) with B \u003d 1. Since the spectrum of signals with a limited duration has an unlimited length, then various methods and tricks.

Increasing the base in NPS is achieved by additional modulation (or keying) in frequency or phase at the time of the signal duration. As a result, the spectrum of the signal F (while maintaining its duration T) is significantly expanded. Additional intra-signal modulation by amplitude rarely used.

In communication systems with NLS, the width of the spectrum of the emitted signal F is always much greater than the width of the information message spectrum.

SPS have been used in broadband systems communications (SHPSS), because:

allow you to fully realize the benefits best practices signal processing;

provide high noise immunity of communication;

· allow you to successfully deal with multipath propagation of radio waves by separating the beams;

allow simultaneous work many subscribers in a common frequency band;

allow you to create communication systems with increased secrecy;

provide electromagnetic compatibility(EMC) SHPSS with narrowband radio communication and broadcasting systems, systems television broadcasting;

provide best use spectrum in a limited area compared to narrowband communication systems.

Noise immunity SHPSS

It is determined by the well-known relation that relates the signal-to-noise ratio at the receiver output q 2 with the signal-to-noise ratio at the receiver input ρ 2:

q 2 \u003d 2Вρ 2 (2)

where ρ 2 = R s /R p (R s, R p - NPS power and interference);

q2 = 2E/ N p,E - NPS energy, N p - interference power spectral density in the NPS band. Accordingly, E \u003d P with T , a N p \u003d P p / F;

B - base of the ShPS.

The signal-to-noise ratio at the output q 2 determines the operational characteristics of the reception of the NPS, and the signal-to-noise ratio at the input ρ 2 determines the energy of the signal and interference. The value of q 2 can be obtained according to the system requirements (10...30 dB) even if ρ 2<<1. Для этого достаточно выбрать ШПС с необходимой базой В, satisfying (2). As can be seen from relation (2), the reception of NLS by a matched filter or correlator is accompanied by signal amplification (or interference suppression) by 2 V times. That is why the value

To NPS = q 2 /ρ 2 (3)

is called the processing gain of the NPS or simply the processing gain. From (2), (3) it follows that the processing gain K NPS = 2V. In the SPSS, the reception of information is characterized by the signal-to-noise ratio h 2 = q 2 /2, i.e.

h 2 \u003d Bρ 2 s (4)

Relations (2), (4) are fundamental in the theory of communication systems with NLS. They are obtained for interference in the form of white noise with a uniform power spectral density within a frequency band, the width of which is equal to the width of the NLS spectrum. At the same time, these relations are valid for a wide range of interference (narrow-band, impulse, structural), which determines their fundamental importance.

Thus, one of the main purposes of communication systems with NLS is to ensure reliable reception of information under the influence of powerful interference, when the signal-to-noise ratio at the receiver input ρ 2 can be much less than one. It should be noted once again that the above relations are strictly valid for interference in the form of a Gaussian random process with a uniform power spectral density (“white” noise).

The main types of SHPS

A large number of different NLSs are known, the properties of which are reflected in many books and journal articles. SPS are divided into the following types:

frequency modulated (FM) signals;

· multifrequency (MF) signals;

· phase-shift keyed (PM) signals (signals with code phase modulation - QPSK signals);

Discrete frequency (DF) signals (signals with coded frequency modulation - CFM signals, frequency-shift keyed (FM) signals);

· Discrete composite frequency (DSCH) (composite signals with coded frequency modulation - SKChM signals).

Frequency modulated (FM) signals are continuous signals, the frequency of which varies according to a given law. In Figure 1a, an FM signal is shown, the frequency of which varies according to the V-shaped law from f 0 -F / 2 to f 0 + F / 2, where f 0 is the central carrier frequency of the signal, F is the spectrum width, in turn, equal to the deviation frequency F = ∆f d. The duration of the signal is T.

Figure 1b shows the frequency-time (f, t)-plane, on which the hatching approximately shows the distribution of the FM signal energy over frequency and time.

The base of the FM signal by definition (1) is equal to:

B = FT=∆f d T (5)

Frequency-modulated signals have found wide application in radar systems, since for a particular FM signal, a matched filter can be created on devices with surface acoustic waves (SAWs). In communication systems, it is necessary to have many signals. In this case, the need for a quick change of signals and switching of the formation and processing equipment leads to the fact that the law of frequency change becomes discrete. In this case, FM signals are transferred to HF signals.

Multifrequency (MF) signals (Figure 2a) are the sum N harmonics u(t) ... u N (t) , whose amplitudes and phases are determined in accordance with the laws of signal formation. On the frequency-time plane (Figure 2b), hatching highlights the energy distribution of one element (harmonics) of the MF signal at frequency f k . All elements (all harmonics) completely overlap the selected square with sides F and T. The signal base B is equal to the area of ​​the square. The width of the spectrum of the element F 0 ≈1/Т. Therefore, the base of the MF signal

B = F/F 0 =N (6)

Figure 1 - Frequency-modulated signal and time-frequency plane

i.e., coincides with the number of harmonics. MF signals are continuous and it is difficult to adapt digital technology methods for their formation and processing. In addition to this disadvantage, they also have the following:

a) they have a poor crest factor (see Figure 2a);

b) to get a large base AT it is necessary to have a large number of frequency channels N. Therefore, MF signals are not considered further.

Phase shift keyed (PM) the signals represent a sequence of radio pulses, the phases of which change according to a given law. Usually the phase takes two values ​​(0 or π). In this case, the RF FM signal corresponds to the video-FM signal (Figure 3a), consisting of positive and negative pulses. If the number of pulses N , then the duration of one pulse is equal to τ 0 = T/N , and the width of its spectrum is approximately equal to the width of the signal spectrum F 0 = 1/τ 0 = N/Т. All elements overlap the selected square with sides F and T. Base of the PM signal

B = FT =F/τ 0 =N, (7)

those. B is equal to the number of pulses in the signal.

The possibility of using FM signals as NPS with bases B = 10 4 ... 10 6 is limited mainly by processing equipment. When using matched filters in the form of SAW devices, optimal reception of FM signals with maximum bases Vmax = 1000 ... 2000 is possible. FM signals processed by such filters have wide spectra (about 10 ... 20 MHz) and relatively short durations (60 ... 100 µs). The processing of FM signals using video-frequency delay lines when transferring the signal spectrum to the video frequency region allows obtaining bases B = 100 at F≈1 MHz, T ≈ 100 µs.

Matched filters based on charge-coupled devices (CCDs) are very promising. According to published data, using matched CCD filters, it is possible to process PM signals with bases of 10 2 ... 10 3 with signal durations of 10 -4 ... 10 -1 s. The CCD digital correlator is capable of processing signals up to a base of 4∙10 4 .

Figure 2 - Multi-frequency signal and time-frequency plane

Figure 3 - Phase Keyed Signal and Time-Frequency Plane

It should be noted that it is advisable to process PM signals with large bases using correlators (on LSI or CCD). At the same time, B = 4∙10 4 seems to be the limit. But when using correlators, it is necessary first of all to solve the problem of accelerated entry into synchronism. Since PM signals make it possible to widely use digital methods and techniques for generating and processing, and such signals can be realized with relatively large bases, therefore, PM signals are one of the promising types of NLS.

Discrete frequency (DF) the signals represent a sequence of radio pulses (Figure 4a), the carrier frequencies of which change according to a given law. Let the number of pulses in the DC signal be M , the pulse duration is T 0 =T/M, its spectrum width F 0 =1/T 0 =M/T. Above each pulse (Figure 4a) its carrier frequency is indicated. On the time-frequency plane (Figure 4b), hatching highlights the squares in which the energy of the DC signal pulses is distributed.

As can be seen from Fig. 4b, the energy of the DC signal is distributed unevenly on the frequency-time plane. Base of RF signals

B \u003d FT \u003d MF 0 MT 0 \u003d M 2 F 0 T 0 \u003d M 2 (8)

since the momentum base is F 0 T 0 = l. From (8) follows the main advantage of HF signals: to obtain the required base Number of channels M = , i.e., much less than for MF signals. It is this circumstance that has led to attention to such signals and their use in communication systems. At the same time, for large bases B = 10 4 ... 10 6, it is not advisable to use only HF signals, since the number of frequency channels M = 10 2 ... 10 3, which seems to be excessively large.

Discrete composite frequency (DSCh) the signals are DC signals in which each pulse is replaced by a noise-like signal. Figure 5a shows a video-frequency PM signal, the individual parts of which are transmitted at different carrier frequencies. The frequency numbers are indicated above the FM signal. Figure 5b shows the frequency-time plane, on which the energy distribution of the DFS signal is highlighted by hatching. Figure 5b does not differ in structure from figure 4b, but for figure 5b the area F 0 T 0 = N 0 is equal to the number of PM signal pulses in one frequency element of the DFS signal. DFS signal base

B \u003d FT \u003d M 2 F 0 T 0 \u003d N 0 M 2 (9)

The number of pulses of the total PM signal N=N 0 M

Figure 4 - Discrete frequency signal and time-frequency plane

The DFS signal shown in Figure 5 contains PM signals as elements. Therefore, such a signal will be abbreviated as a DFS-FM signal. DF signals can be taken as elements of the DFS signal. If the base of the element of the DC signal B \u003d F 0 T 0 \u003d M 0 2 then the base of the entire signal B \u003d M 0 2 M 2

Figure 5 - Discrete composite frequency signal with phase shift keying DFS-PM and time-frequency plane.

Such a signal can be abbreviated as DSC-FM. The number of frequency channels in a DFS-FM signal is equal to M 0 M. If the DC signal (see Figure 4) and the DFS-FM signal have equal bases, then they also have the same number of frequency channels. Therefore, the DFS-FM signal has no special advantages over the DC signal. But the principles of constructing a DFS-FM signal can be useful when building large systems of DC signals. Thus, the most promising NSS for communication systems are FM, DC, DFS-FM signals.

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Noise immunity of a radio communication channel with remote stationary objects

Type of work: Essay Subject: TECHNICAL SCIENCES

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Automation. Informatics. Control. Devices UDC 621.396.96

NOISE IMMUNITY OF A RADIO CHANNEL OF COMMUNICATION WITH REMOTE STATIONARY OBJECTS V. V. Aksenov, V. I. Pavlov [email protected]

Submitted by a member of the editorial board, Professor D. Yu. Muromtsev Key words and phrases: indicator functions of interference - communication channel - noise immunity.

Abstract: Mathematical models of signals and intentional interference are considered in relation to a communication channel with remote stationary objects. It is proposed to use a set of indicator functions of interference to improve the noise immunity of a radio communication channel. An example of using the indicator function is presented.

Radio control and communication systems, as a rule, are an integral part of complex control complexes (objects, people) and are intended for the transmission of measurement information characterizing the state vector of controlled objects, the transmission of command and various types of communication information. At the same time, the required accuracy of message transmission, as well as the performance of other functions, must be achieved in a difficult interference environment, which will largely be determined by the noise immunity of the communication channel.

In connection with the difficult criminal situation and the terrorist threat, the stability of the communication channel to the effect of deliberate interference created by third parties in order to distort, suspend or stop the transmission of information is important. Special attention is required for objects of critical importance (for example, main product pipelines) that use open communication channels to monitor their technical condition.

As a rule, for such objects, the nature and structure of the information transmitted over the communication channel (signals from sensors, commands for controlling individual devices) are known. Messages are usually transmitted periodically and in bursts. With the help of electronic intelligence, third parties can accumulate information about the communication mode, frequency bands used, types of signals, modulation, etc. for a long time.

This information can be used both to form a mode of counteraction to the communication system as a whole, and specific intentional interference to the channel. Therefore, to improve noise immunity, it becomes necessary to timely detect the presence of deliberate interference in the received signal and adapt the communication channel to the effect of interference.

As you know, the noise immunity of radio communications (SRS) is achieved through a set of organizational measures, methods and means aimed at ensuring the stable operation of the SRS under the influence of organized (intentional) electronic jamming (REC) interference.

The process of functioning of the SRS under conditions of organized interference in its physical essence can be represented as an electronic conflict, in which, on the one hand, the SRS participate, and on the other, the REB system, which generally consists of an electronic intelligence station (RTR) and the jamming station itself. Figure 1 shows a general block diagram of an electronic conflict.

Considerable attention is paid to the problem of protecting the communication channel from intentional interference. A channel is considered secure if it provides the required indicators of information transmission secrecy and resistance to intentional interference. The model of a protected communication channel (PSC) must additionally contain a model of a specially designed transmitted signal, a model of intentional interference, and methods for combating interference.

Transmitted signal model. In the general case, signals s(t) are transmitted in the ECS under the influence of multiplicative ^(t) and additive?(t) interference (Fig. 1). These interferences should be considered as unintentional. If there are no intentional noises, then at the receiver input, realizations of a random process are observed

x(t)=Kt)s(t)+^(t). (one)

The function ^(t) is a random process, and ^(t) > 0, t e R = . - M .: Radio and communication, 2003. - 640 p.

5. Borisov V. I. Noise immunity of radio communication systems: fundamentals of theory and principles of implementation. — M.: Nauka, 2009. — 358 p.

6. Varakin, L. E. Theory of complex signals / L. E. Varakin. — M.: Sov. radio, 1970. - 376 p.

7. Pavlov, V. I. Optimal detection of changes in the properties of random sequences according to the information of the meter and indicator / V. I. Pavlov // Automation and Telemechanics. - 1998. - No. 1. - S. 54−59.

Stability to Hindrances of the Radio Channel of Communication with Remote Stationary Objects

V.V. Aksenov, V. I Pavlov

Department "Design of Radio Electronic and Microprocessor Systems", TSTU-

Key words and phrases: communication channel-indication functions of hindrances-stability to hindrances.

Abstract: Mathematical models of signals and deliberate hindrances with reference to a communication channel with remote stationary objects are considered. The use of set of indication functions of hindrances for increase of stability to hindrances of the channel of radio communication is offered. The example of use of indication function with some deliberate hindrances is presented.

Storungsstabilitat des Funkkanals der Kommunikation mit den entfernten Stationarobjekten

Zusammenfassung: Es sind die matematischen Modelle der Signale und der vorausgesehenen Storungen in bezug auf den Kommunikationskanal mit den entfernten Stationarobjekten betrachtet. Es ist die Benutzung der Gesamtheit der Indikatorfunktionen der Storungen fur die Erhohung der Storungsstabilitat des Funkkanals der Kommunikation vorgeschalagen. Es ist das Beispiel der Benutzung der Indikatorfunktion dargelegt.

Rigidite aux erreurs de la chaine de liaison de radio avec les objets stationnaires eloignes

Resume: Sont examines les modeles mathematiques des signaux et des erreurs deliberees conformement a la chaine de liaison de radio avec les objets stationnaires eloignes. Est proposee l'utilisation de l'ensemble des fonctions indiquees des erreurs pour l'augmentation de la rigidite aux erreurs de la chaine de liaison de radio, est presente l'exemple de l'utilisation de la fonction indiquee.

Authors: Aksenov Viktor Vladimirovich — post-graduate student of the department "Design of radio-electronic and microprocessor systems" — Pavlov Vladimir Ivanovich - doctor of technical sciences, professor of the department "Design of radio-electronic and microprocessor systems", FGBOU VPO "TSTU".

Reviewer: Shamkin Valery Nikolaevich - Doctor of Technical Sciences, Professor of the Department of Design of Radioelectronic and Microprocessor Systems, FGBOU VPO "TSTU".

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