Linear frequency modulation radar signal processing method based on compressed sensing

Abstract

The invention discloses a linear frequency modulation radar signal processing method based on compressed sensing. The method comprises the steps of (1) emitting a linear frequency modulation signal to a radar and preprocessing an echo signal, which means that the deramping processing of the echo signal is carried out, a difference frequency signal is outputted, and a signal model of deramping processing is established in a time domain, (2) according to the sparsity of the difference frequency signal in a frequency domain, constructing a sparse conversion matrix, and establishing a sparse representation model of the radar echo signal, (3) constructing a measurement matrix, and realizing the projection transformation of a difference frequency sparse signal to a low dimensional space, and (4) using an orthogonal matching pursuit (OMP) algorithm, reconstructing a radar difference frequency signal, and efficiently obtaining target information. Accoding to the method, the compression of radar echo signal data can be fundamentally realized, the change of a sparse model according to a radar observation distance is not needed, finally the target information is obtained, and the method is suitable for the echo signal processing of an actual radar.

Description

technical field [0001] The invention relates to the technical field of radar signal processing, is a method for realizing radar echo signal processing based on compressed sensing for linear frequency modulation signals, and is suitable for actual radar signal processing. Background technique [0002] Radar typically improves resolution by emitting broadband or ultra-wideband signals. Linear Frequency Modulation (LFM) pulse signal is the earliest and most widely used form of radar signal. The transmission of broadband LFM pulse signal has caused great pressure on the data acquisition, transmission, storage and real-time processing of the radar system. [0003] In 2004, Donoho, Candes and Tao et al. proposed the theory of Compressive Sensing (CS), which is a brand-new signal acquisition and processing theory, which realizes signal compression in the process of signal sampling at the same time, which is much lower than that of Nyquist. Sampling at the highest sampling rate and...

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