| The pulse compression radar emits large time-bandwidth product signals in the transmitter, while in the receiver it compresses the return signals with matched filter. The pulse compression techniques can result in high range resolution, and also provide a large processing gain for the radar. Pulse compression radar is a kind of low probability of intercept (LPI) radar. The term LPI is that property of radar that, because of its low power, wide bandwidth, or other design attributes, makes it difficult to be detected by means of a passive intercept receiver. The LPI requires the increase in capability of modern intercept receivers to detect and locate a radar emitter. The wideband digital receiver concerning its advantage over traditional crystal video receiver is in ergent need to develop. It digitizes the intermediate frequency or radio frequency radar signal directly, preserves its frequency and phase modulation information, and makes it easy to detect, store and analyze the radar signal.The contermeasures to pulse compression signal are detection and interception, and then identification. Modern electromagnetic environment is dense, interleaving with complex time-varying waveforms. There are simple pulse modulation signals with relatively narrow bandwidth, also pulse compression signals with large bandwidth. Their carrier frequencies and bandwidth are unkown to the intercept receiver. Therefore the reception of various types of radar signals is the first problem to deal with in wideband receiver. Digital channelization receiver can process simultaneous arriving signals. Uniform channelization receiver is a kind of mature wideband digital receiver. Its implementation is efficient. Unfortunately, because its channels are unchangeable and restrictly uniform, it dose not meet the EW environment and needs some improvements.Once the signals are intercepted, modern signal processing algorithms can be used to analyze the intrapulse information and extract the modulation parameters. There are three kinds of widely used pulse compression signals, phase shift keying (PSK) signals, linear frequency modulation (LFM) signals, and nonlinear frequency modulation (NLFM) signals. PSK signals include BPSK signals and MPSK signals, and QPSK signals are frequently used MPSK signals. Parameters of PSK to be estimated include carrier frequency, code rate and coding sequence. LFM and NLFM signals can be modeled as polynomial phase signals (PPS). LFM signals are second order PPS signals, while NLFM signals are high order PPS signals. Therefore FM signals can be identified by estimating each order phase coefficient.In order to intercept and recognize pulse compression radar signals on wideband digital receiver (WDR) platform, several subjects were studied in detail, including dynamic digital channelization techniques, dynamic range extension of WDR, modulation parameter estimation algorithms for PSK and FM radar signals.In terms of wideband channelization techniques, the drawback of recent proposed channelization receiver when receiving multi-channels which are non-uniformly distributed and dynamically changing in wideband received signal was pointed out. Dynamic channelization method was proposed. Two efficient implementation structures based on DFT filter banks and short time discrete Fourier transform respectively were presented. Both structures can be used to channelize dynamic changing and non-uniformly distributed channels adaptively. All channels can be processed in parallel and real-time. Both structures can be implemented in field-programmable gate array (FPGA) chips. Implementation schematics of key modules were also presented.In terms of extending dynamic range of WDR, digital automatic gain control (DAGC) was used. The limitation factors of WDR dynamic range such as microwave front-end thermal noise, amplifier-link noise factors and nonlinear characteristics, super high speed ADC limited quantification accuracy were thoroughly researched. Two intermediate frequency DAGC systems were presented based on analysis of DAGC control algorithms. In combination of multi-rate signal processing technology, an efficient Hilbert transform method for envelope extraction was proposed. This method converts the high speed ADC data flunt to low speed data flunt, which then can be processed by FPGA.In terms of PSK signal parameters estimation, a good estimation procedure with comprehensive application of cyclic correlation theory and continous wavelet transform was presented. Firstly cyclo-spectrum method was used to carry out blind estimation of PSK signal carrier frequency and coding rate for its good anti noise performance. Then the PSK signal was shifted to base band with frequency estimate. Haar wavelet transform method was used to extract phase jump points of PSK signal, and its performance was studied in detail. It was pointed out that wavelet transform maxima point always appears at phase jump point when carrier residual approaches zero. Therefor the phase jump points can be extracted via wavelet transform maxima. Influence of carrier residual on the algorithm was thoroughly studied. Selection of wavelet scale when carrier residual exists was given. An algorithm for PSK coding sequence recognition based directly on phase function was presented. Large number decision was introduced to eliminate phase-wrapping phenomenon caused by noise. The phase difference between neighboring codes was estimated according to phase function. The accumulative phase induced by residual carrier was estimated and subtracted from the phase difference. Then the phase jump of neighboring codes was estimated.In terms of FM radar signal parameter estimation, polynominal phase modeling method was used. Product high-order-ambiguity function to estimate phase coefficients of PPS signals suffers from detection missal and error propagation effect. Detection missal condition was deduced, and an improved method called PAHAF was presented. The error propagation effect was induced by limited frequency resolution of FFT, which can be improved by Chirp-Z transform.
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