LFM signal detection based on STFT and frequency-domain GOSBOS-CFAR in low SNR

摘要

According to the continuous time-frequency characteristic of linear frequency modulated (LFM) signals, a detection method based on Short-Time Fourier Transform (STFT) and a new Constant False Alarm Rate (CFAR) detector is proposed. The input signals are short-time Fourier transformed to achieve coherent integration of frequency-shift sample sequences with complex envelopes, modular square of which are to be CFAR detected in frequency domain. On the basis of GO, the proposed Greatest Of and Statistics-Based Order Statistics (GOSBOS) algorithm exploits the a priori information provided by statistics of former frames for threshold adaptation. The scheme takes advantage of both OS's superior detection performance and GO's noticeable ability to control false alarms under non-homogeneous background. Simulation results show its fine detection performance in −15dB signal to noise ratio (SNR) condition, which can well meet the need of electronic reconnaissance.