Constant false alarm rate vehicle-mounted radar target detection method and device, equipment and storage medium

Abstract

The invention provides a constant false alarm rate vehicle-mounted radar target detection method and device, electronic equipment and a computer readable storage medium. The method comprises the steps of carrying out the square law detection of radar echo signal data, loading the radar echo signal data into a reference unit, carrying out the sorting, carrying out the segmentation processing, and calculating the standard deviation of each segment of data, calculating the standard deviation of each segment of data and the statistical distribution difference of the first segment of data to obtain a JS divergence value, calculating a segmentation threshold according to the JS divergence value, deleting the data segments greater than the segmentation threshold and counting the first number of the data segments, performing mathematical operation on the first number and a preset false alarm rate to obtain a nominal factor, and performing addition operation on the data segments smaller than the segmentation threshold to obtain a sum value, multiplying the sum value by a nominal factor to obtain a detection threshold, and judging that a target exists when the data of the detected unit is greater than the detection threshold. According to the method, the large value rejection number can be adaptively determined according to the change of an actual detection environment, the detection efficiency and accuracy are improved, and meanwhile, the method has relatively good false alarm control capability.

Description

technical field [0001] The present application relates to the technical field of signal detection, and in particular to a vehicle radar target detection method with a constant false alarm rate, a vehicle radar target detection device with a constant false alarm rate, a vehicle radar target detection electronic device with a constant false alarm rate, and a computer Read the storage medium. Background technique [0002] In complex traffic conditions, low signal-to-noise ratio target information is extracted from the background noise, which seriously affects the target detection ability. The tracking-before-detection algorithm is one of the key technologies for accurate detection and tracking of low signal-to-noise ratio targets. Coherent or non-coherent accumulation is performed to achieve the purpose of extracting the target trajectory from the noise background. [0003] Constant false alarm rate detection (CFAR) is to use adaptive threshold estimation technology to automa...

AI Technical Summary

Problems solved by technology

But these detectors have a common shortcoming, they are all proposed for a certain clutter background, while improving the detection performance in this background, it is at the expense of CFAR damage in other backgrounds

[0004] With the continuous development of scientific research, E-CFAR, CCA-CFAR, and GCMLD-CFAR have appeared one after another. However, this type of detector compares the reference unit with the detection threshold that satisfies a certain type of error pruning probability, and deletes more than the detection threshold. The reference unit often has a large amount of calculation, and requires a priori information on the number of interference targets, or artificially sets a large value to delete the number, which cannot be adaptively extracted from the environment

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