| Information technique plays more and more important role in advanced military fields. It becomes a key factor determining the war victory or defeat. Information warfare is now a main battle form of the modern war. Electronic warfare, whose intention is to control the electromagnetism, is the most important core subsystem of information warfare. Communications Counter-Measures is a main part of electronic warfare.Signal processing theory using in military Communications Counter-Measures has been making great progresses. This is by two reasons: the first, as the development of military communication technologies, it transit from digital to software implementation, intelligence, Broad Band implementation and network implementation. Many new technologies such as adaptive frequency hopping, burst communication, broadband modulation and complex coding accelerate the research about pertinence algorithms of signal sense and signal processing. The second, three hotspots of modern signal processing-spectrum estimation, High-Order Statistics (HOS) and time-frequency analysis theory become more and more consummately and being used in communication jamming and anti-jamming field. Besides, the usage and the development of the all-digital receiver and the software radio technology provide the application platform for modern signal processing technology.This dissertation discussed the signal processing theory and technology using in military Communications Counter-Measures. In order to construct a system to sense and recognize the enemy transceivers, we proposed many algorithms to emulate signal extraction, signal modulation recognition, blind spread spectrum signal detection and parameter estimation, and the fingerprint identification of the transceiver. It deals with the communication signal processing and non-stationary signal processing under non-cooperation situations. Many technologies such as HOS, pattern recognition, clustering and Neural Network (NN) are used here for signal processing.Research background, research goal and the whole system scheme are given in the first chapter, then all kinds of algorithms, emulations and performance analyses of the subsystems are given in chapters later.After we received the mixed signals of transceivers more than one, we estimate the number of signals and the directions of arrival (DOA), form the beams of one transceiver, focus the partition points between the noises, the transients generated when a transceiver turned on and the communication signals. Here we proposed two algorithms, one is a improved algorithm which can be used to estimate the number of signals based on the Gerschgorin theory, the other is a signal focusing algorithm based on the singularities of signals. The whole preprocessing procedure is emulated here.For communication signals, we detect if there exist spread spectrum signals such as Direct Sequence Spread Spectrum (DSSS) or Frequency-Hopped (FH) signals and estimate their parameters if the DSSS or FH signals exist. If there exist normal communication signals, we identify the modulation types. Here a modulation recognition algorithm is proposed which can be used to identify 7 kinds of analog modulations such as AM, DSB, USB, LSB, CW, FM, AM-FM and 7 kinds of digital modulations such as 2ASK, 4ASK, 2FSK, 4FSK, 2PSK, 4PSK, 16QAM. For DSSS signals, we proposed two algorithms, one is a hypothesis test algorithm that can be used to detect if there are DSSS signals, the other is a symbol period estimation algorithm using the cycle-stationary feature of DSSS signals. For FH signals, we proposed two algorithms too, one is a signal detection algorithm based multiple-hop autocorrelation (MHAC) of FH signals, and the other is a parameter estimation algorithm based on time-frequency analysis.The transients generated just when a transceiver turned on and the fine features of communication signals are regarded as the fingerprints of a transceiver. For transients, we proposed two algorithms, one is a improved clustering algorithm which can be used to classif...
|
PDF Full Text Request