ASC-BSS-Based Parameter Estimation Method for Multiple LFM Pulses With Aliasing Effect From Passive Radar

Abstract

Accurate parameter estimation of linear frequency modulation (LFM) pulses is important for passive radar detection. However, due to the increasingly complex electromagnetic environment, the pulse density of the received signal from noncooperative transmitters increases, which may cause aliasing effect for multiple LFM pulses in both the time–frequency domain and the fractional Fourier transform (FrFT) domain. In addition, the low probability of intercept technology results in the low signal-to-noise ratio (SNR) of the received signal. In order to achieve effective parameter estimation of aliasing LFM pulses under low-SNR conditions, this article proposes an aliasing removal algorithm based on analytic signal construction (ASC) and blind source separation (BSS). Specifically, the analytical expressions of the aliasing LFM pulses at different FrFT transformation angles are first derived. Then, ASC is applied to construct the virtual channel signal, and subsequently, BSS is utilized to realize aliasing removal in the FrFT domain. Finally, pulse modulated parameters (including pulsewidth, initial frequency, and chirp rate) can be effectively estimated. Simulation experiments prove the validity of the proposed method.