Study On Theories And Algorithms Of Intrapulse Analysis And Processing Of Radar Signals

In the Electronic Warfare, reconnaissance and jamming to the threatening radar was a very important subject. The analysis of those intercepted radar signals was a must. Intrapulse analysis of radar signals plays a significant role in the radar signal analysis. Through the Intrapulse analysis,the performance of the enemy radar can be evaluated and the support can be provided to the operational force, such as the method of attack and defense. This thesis studies several key problems of radar intrapulse analysis. The main contributions are summerized as follows:Firstly, a modified Rife (MRife) algorithm is proposed. It is operated by moving the signal frequency to the central region of two neighboring discrete frequencies and then the frequency is estimated by Rife algorithm. Simulation results show that the performance of MRife does not fluctuate with the distribution of signal frequency, RMSE(root mean square error) is less than that of one iteration of Newton's method, and close to that of two iterations. Under the condition of low signal-to-noise ratio (SNR), MRife has no divergence problem and is more stable than Newton's method.Secondly, the divergence problem of Newton Iteration with Rife estimation as its initial value is illustrated. In order to solve the problem, the starting value of Newton's method is changed to MRife estimation. Through this modification, the RMSE of frequency estimation is close to CRLB throughout the frequency band and the performance is steady.Thirdly, frequency estimation algorithms of sinusoid applied to all phase spectrum analysis are studied. First the structure of all phase spectrums is analyzed and the all phase spectral interpolation formula is put forward. Then the modified all phase spectral interpolation algorithm is presented by frequency shift. Compared with the all phase frequency correction method, the spectral interpolation algorithm is more accurate and achieves better performance under medium and low SNR conditions.Fourthly, a symbol rate estimator based on correlation receiver and blind symbol rate estimation method based on multi-scale Haar wavelet transform are presented. According to the run length distribution characteristic of multi-phase-shift keying (MPSK) signals, the method based on correlation receiver calculates the assembly average of the position of spinodals, which are the output of correlation receiver. Then the symbol rate can be estimated. For the method of Haar wavelet transform, three wavelet scales are choosed according to signal bandwidth. The phase jumps, which are the output of the receiver, are detected with the multi-scale Haar Wavelet. The symbol rate is extracted by Fourier transform to the detection results. These two algorithms can operate without prior knowledge and realize the real blind estimation.Fifthly, a blind carrier frequency estimation algorithm of MPSK signals is proposed. First the carrier frequency and symbol rate are estimated without prior knowledge. Then the signals are transformed to the baseband. Because the phase of baseband-modulated PSK signal is a piecewise linear function and the slope coefficient of every segment is a linear function of frequency offset, the multi-segment line can be transformed to a straight-line and then the least squares fitting method is applied to estimate the slope coefficient. The simulation results show that this method can accurately estimate the carrier frequency without prior knowledge.Sixthly, a maximum-likelihood-based recognition algorithm of modulation mode of the polyphase-coded radar signals and a general algorithm of identification and parameter estimation are presented. For the maximum-likelihood-based algorithm, the carrier frequency and symbol rate are estimated first, and then the local reference signals can be generated and a correlation receiver can be designed. Thus the decision was made based on the maximum likelihood criterion. The modulation type of the reference signal, which generates the maximum output, is that of the received signal. For the general identification and parameter estimation algorithm, the reference signals are multiplied by the conjugated received signals. When the reference signals and the received signals have the same modulated mode, the result of the multiplication is a sinusoid, thus the polyphase-coded signals can be classified. Finally the carrier frequency can be obtained by estimating the frequency of the sinusoid.