| Recently, Low Probability of Intercept (LPI) radar technique has improved rapidly. Because the traditional intercept receiver devices are difficult to detect LPI radar signals, therefore, the development of new methods for detecting LPI radar signals is of great significance. In this paper, we investigate the LPI radar signals and the methods for LPI radar signals detection, the main contents are as follows.Firstly, we introduce three typical LPI radar signal detection methods, the Matching template method, the Wigner-Ville distribution method and the HOS based method. Then we perform simulations to detect the Linear Frequency Modulation Continuous Wave (LFMCW) signal, the Binary Phase Shift Keying (BPSK) signal, the P4 code, the Costas frequency hopping (HF_C) and Phase Shift Keying/Frequency Shift Keying with Costas (PSK/FSK_C) signals, using WVD and HOS methods.Secondly, we investigate a new method, which is based on signal de-noising and Quadrature Mirror Filter Bank (QMFB), for LPI signal detection. This new method can both avoid the cross terms and realize Multi- resolution analysis character of wavelet. Based on this method, we can obtian different components from different output layers. This means that we are able to observe the signal plot from lower layers (time domain) and details from higher layers (frequency domain) .Finally, we use QMFB method to detect the LFMCW, BPSK, Polyphase, HF_C and FSK/PSK_C signals via simulations. By analyzing the outputs at different layers of the tree, we can extract the following LPI waveform parameters: carrier frequency, modulation bandwidth, modulation period, code period and the phase shift. Based on these parameters, further processing can be conducted to identify and classify the LPI waveform. Although HOS based method can reduce the effect of the noises, the QMFB also can perform similarly in low SNR with multi-layer autocorrelation and wavelet de-noising. The above proves that QMFB is an effective method for LPI signal detection. |
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