Study On Parameter Estimation Of LPI Radar Signals Of LFM Class

With the continuous progress of radar technology, Low Probability of Intercept (LPI) radar signal has been widely used in the application of the new system radar. As the other party of electronic warfare, the current electronic reconnaissance system face the serious difficulties and challenges. Because of low signal-to-noise ratio, diversified signals, variable parameters, the estimation precision of tradition signal parameters estimation algorithms decreases rapidly, even invalid. Therefore, researches on how to estimate the LPI radar signal parameters effectively in complex environment has important theory significance and the military application value.This dissertation mainly deals with the parameter estimation of LPI radar signals of LFM class, including Linear Frequency Modulated (LFM) signals, Linear Frequency Modulated Continuous Wave (LFMCW) signals and the polyphase codes which derived from LFM waveforms. This paper focuses on the study of time-frequency analysis and other time-frequency transform algorithms, and how to estimate the signal parameters, such as carrier frequency, frequency modulation rate and modulation period. Combined with the theory analysis and simulation experiments to verify these algorithms, in-depth analysis the estimation performance and applicable conditions of the algorithm, explore the improved algorithm and computer implementation method. The main contents are as follows:Chapter 1 discusses the background and significance of our topic. Then the research status of parameter estimation of signals of LFM class is presented.Chapter 2 introduces the basic theories of LPI radar and it’s parameter estimation. The definition of LPI is given firstly. Radar intercept factor is discussed in detail, and the key factors which affect the performance of LPI radar is illustrated. The theory of pulse compression which the key to LPI radar is provided. Then, From the perspective of electronic reconnaissance the basic theory of LPI radar parameter estimation is discussed, including signal type, signal parameter estimation methods and the evaluation methodology of estimation performance. A brief review of signal parameter estimation methods such as time frequency analysis methods, cyclostationarity approaches, and spectrum estimation methods is presented. Finally, the Cramer-Rao (CRB) bound and relative root mean square error are discussed.The parameter estimation of LFM signal is studied in Chapter 3. First, the signal model and the signal charateristics of time domain and frequency domain are analyzed. Based on the time frequency graph of signal, the Wigner Hough Transform (WHT) and the Radon-Ambiguity Transform (RAT) are researched separately, and the performance of these two methods are analyzed,too. Then, the Fractional Fourier Transform (FRFT) method, the matched signal transform method and the Lv’s Distribution (LVD) method for estimating the LFM parameters are studied. Aim at the problem which caused by frequency deviation of the MST algorithm, an improved method based two dimensional plane searching is proposed, it can improve the parameter estimation performance effectively. The computational efficiency and estimation accuracy of the methods are analyzed by simulation experiments, the validity of the proposed method is demonstrated.In Chapter 4, the parameter estimation of LFMCW signal is studied. The mathematic models, practical intercept signal waves, frequency domain and time frequency domain features of sawtooth wave LFMCW radar and triangular wave LFMCW radar are analyzed firstly. The parameter estimation method based Short-Time Fourier Transform (STFT) graph is researched in detail. The instantaneous frequency is got by the peak line, then the parameters can be estimated. And on this basis, an improved SM algorithm based self adaption window width is proposed, which can advance the parameter estimation performance. Considering the low Signal to Noise Ratio (SNR) condition, two period estimation methods are presented. One is based on cyclic autocorrelation, and the other is based on time domain correlation. Furthermore, the method based Discrete Chirp-Fourier Transform (DCFT) and coherent average which can estimate the carrier frequency and frequency modulate rate is proposed, and it has higher estimation accuracy under the low SNR. The correctness and effectiveness of the proposed method is proved by the simulation experiments at last.Chapter 5 researches the parameter estimation of polyphase codes. The mathematic models, time domain, frequency domain and phase features of the polyphase codes, including Frank, P1, P2, P3 and P4, are analyzed. The Wigner-Ville distribution (WVD) of polyphase codes is derived. Two parameter estimation methods of polyphase codes based on WHT and based on RAT are proposed, respectively. Furthermore, the time frequency rate distribution is studied in detail. The time frequency rate distribution of polyphase codes is deduced and analyzed. The energy concentration of different time frequency distribution are discussed by extend factor, and an algorithm based on Time-Frequency Rate (TFR) is presented to estimate the parameters of polyphase codes. The estimation performances are analyzed by simulation experiments, the results verify the proposed method has better performance under low SNR circumstance.The whole dissertation is concluded in Chapter 6, and some further research issues are pointed out.