Detection and Estimation Algorithm for Marine Target With Micromotion Based on Adaptive Sparse Modified-LV’s Transform

2022 
Due to the complex marine environment and high-order frequency modulation (FM) on radar echo from the micromotion of the target, the effective and robust detection of a marine target with micromotion under heavy sea clutters’ background is a challenging task. In this article, we propose a novel detection and estimation algorithm based on adaptive sparse modified-Lv’s transform (ASMLVT). First, the micro-Doppler (m-D) characteristics of marine targets are employed and modeled as quadratic frequency-modulated (QFM) signals. Second, we modify the 2-D robust sparse Fourier transform (2-D-RSFT) and make it adaptive to the sea clutters’ background, namely, 2-D adaptive sparse Fourier transform (2-D-ASFT). Then, we substitute the 2-D Fast Fourier transform (2-D-FFT) operation with 2-D-ASFT in the modified-Lv’s transform (MLVT). The proposed algorithm can not only achieve good energy accumulation and accurate parametric estimation for marine targets with micromotion but is also robust to the heavy sea clutters and can greatly reduce false alarms. Besides, it has a good cross-term suppression ability to detect multitargets. Experiments with simulated and real radar datasets show that the proposed algorithm can effectively detect and estimate multitargets with micromotion under heavy sea clutter and low signal-to-clutter ratio (SCR) background.
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