Stealth Radar Signal Detection And Parameter Estimation Method

To realize the stealth function, the stealth equipment adopts the absorbent material and special shape design. Furthermore, they try their best to spread the energy of radar signals to multidimensional domains, including time, frequency and space domains, etc., making radar signals have low probability of intercept (LPI). The reconnaissance receiver, which is designed for the stealth radar signals, should have a broad instantaneous monitoring bandwidth to ensure a high probability of intercept in the frequency domain, and be able to deal with the stealth radar signals with complex signal forms or combined modulation. First, when the instantaneous monitoring bandwidth reaches up to tens of GHz, we design a new reconnaissance receiver to receive the stealth radar signals with a high probability of intercept in the frequency domain using a low sampling rate analog-to-digital converter. Second, under the condition of negative signal-to-noise ratio (SNR), this dissertation focuses on the detection and parameter estimation of some classical stealth radar signals based on the signal features. The main contributions of this dissertation are as follows:1) When the monitoring bandwidth is up to tens of GHz, first, we propose a synchronization Nyquist folding receiver (SNYFR) using binary phase shift keyed (BPSK) signal as the local oscillator signal (LOS), namely, BPSK-SNYFR. This structure solves the problem of the synchronization difficulties when estimating the Nyquist zone (NZ) of the output signal of the Nyquist Folding Receiver (NYFR). Second, because the nature of the BPSK-SNYFR is that it can modulate different code information in different NZs, we estimate the NZ and frequency of the frequency agile (FA) stealth radar signal.2) We use the generalised time-frequency representation of Zhao-Atlas-Marks (ZAM-GTFR) to realize the parameter estimation of2FSK/BPSK stealth radar signal. The probability of correct estimation (PCE) of the code rate can reach90%when the SNR is-2dB. We also derive the ZAM-GTFRs of different kinds of signals, and extract the sharp negative peak and ridge as the feature. Based on the Hough transform (HT), polynomial curve fitting and fast Fourier transform (FFT), we finish the detection and parameter estimation of S-cubed stealth radar signal. This algorithm works well when the SNR is above3dB.3) For the S-cubed stealth radar signal, the phase difference and modified matched signal transform (MMST) are able to represent the characteristics of the signal. We use the phase difference to extract the instantaneous frequency (IF) of S-cubed signal. We can also use polynomial curve fitting to complete the estimation of the initial frequency and chirp rate. Moreover, with the known information of discrete phase code, we can estimate the period number. Based on the MMST, when the signal is matched, we can detect the signal and estimate the chirp rate in the space domain. The PCE of the chirp rate can reach90%when the SNR is above-4dB.