Performance Of Different Radar Launch Waveform Recursive Minimum Mean Square Error Algorithm With Multi-adaptive Pulse Compression Algorithm

The frequency band congestion has become an important problem in radar and communication fields In this dissertation, we firstly give the Reiterative Minimum Mean-Square Error algorithm for solo-radar, and then derive the Multistatic Adaptive Pulse Compression algorithm for multi-radar. We present several simulations to examine the performance three different radar signals, and achieve some helpful results. The main contents of this paper are as follows.Firstly, we investigate three different radar signals, the linear frequency modulation signal(LFM), combined signal of Barker codes and LFM, combined signal of 4 phase-coded signal and LFM, and analyze their characteristics.Secondly, we investigate Reiterative Minimum Mean-Square Error algorithm and Multistatic Adaptive Pulse Compression algorithm. Respectively, and give the system model of Multistatic Radar.Thirdly, we compare the performance of the above two algorithms with the conventional algorithm for three different radar signals. The results show that the two new algorithms, can offer lower the sidelobe to the noise level, and can improve the multi-target detection ability. Among the three signals, combined signal is superior to the LFM signal in terms of lower noise power. In the case of mutistatic radar, combined signal with Barker codes and LFM can offer the best performance. Their noise level is 3-5db lower than the other two signals.Finally, in the presence of Doppler shifts, we compare the performance of the RMMSE and MAPC. In the presence of Doppler shifts, the algorithm of Doppler shifts will produce wider mainbeam, therefore, affecting its accuracy. For the case of multistatic radar, the anti-noise ability and target-inspect ability of MAPC is still outstanding, meanwhile, combined signal of Barker codes and LFM performance is the best, whose noise level is 5-7db lower than the other two signals.