LFMCW radar target detection method based on dimension reduction approximate message passing

Abstract

An LFMCW radar target detection method based on dimension reduction approximate message passing comprises the following steps: performing, by a receiving end, conventional phase-coherent accumulationon a single-frame baseband data cube to obtain a three-dimensional frequency domain data cube; performing target pre-detection on the data cube after phase-coherent accumulation to obtain pre-detection target trace point information; calculating a dimensionality reduction observation matrix based on trace point information obtained by target pre-detection, arranging the baseband data cube into vectors, and establishing a radar dimensionality reduction observation model; reconstructing a target signal through a generalized approximate message passing algorithm by using a radar dimension reduction observation model; and carrying out constant false alarm detection by utilizing the reconstructed signal. Compared with a traditional target detection method based on fast Fourier transform, the method provided by the invention has higher target detection performance.

Description

technical field [0001] The invention belongs to the technical field of radar target detection, in particular to an LFMCW radar target detection method based on dimensionality reduction approximate message passing (RD-GAMP). Background technique [0002] Traditional linear signal processing methods such as Fast Fourier Transform (FFT) have been widely used in radar signal processing. Taking the vehicle-mounted LFMCW radar as an example, the baseband signal obtained after deskewing the received signal can be modeled as the sum of a series of multipoint frequency signals in the space domain, fast time domain and slow time domain respectively. To improve the signal-to-noise ratio (SNR) of the target, a fast Fourier transform is employed for efficient signal processing. However, in order to reduce the sidelobe of clutter and strong targets, the sampled data are usually weighted before fast Fourier transform, resulting in the loss of SNR. [0003] The method based on compressed ...

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Problems solved by technology

[0006] Aiming at the problem of signal processing loss in the traditional fast Fourier transform target detection method, the present invention provides a LFMCW radar target detection method based on dimensionality reduction approximate message transfer, which reduces the dimension of the signal observation model through target pre-detection and utilizes dimensionality reduction Observation model and generalized approximate message passing algorithm for signal reconstruction and target detection, reducing the signal processing loss of conventional methods and improving target detection performance

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