An Adaptive Threshold Detection Method Based on Point Trace Density Feedback

Abstract

The invention discloses an adaptive threshold detection method based on dot trace density feedback, and relates to the technical field of radar information processing. Including: dividing the detection area into a grid, setting the initial detection threshold; performing threshold detection and dot trace extraction processing on the data to be detected; storing each dot trace in the corresponding grid; if the number of dot traces of the target grid is greater than or equal to the preset dot trace capacity threshold, adjust the detection threshold of the target grid, and repeat the above steps until the number of dot traces of the target grid is less than the dot trace capacity threshold. The self-adaptive threshold detection method provided by the invention is suitable for controlling the number of traces in a non-uniform complex background, and can control the number of traces in the grid to keep a constant range, so as to achieve the processing effect of constant false alarm rate at the point trace level, and not only can Taking into account the false alarm suppression in the clutter area and the weak target detection in the non-clutter area, it can also avoid the missed target detection caused by the filtering of a large number of clutter spots.

Description

technical field [0001] The invention relates to the technical field of radar information processing, in particular to an adaptive threshold detection method based on dot trace density feedback. Background technique [0002] Radar information processing mainly includes two parts: signal processing and data processing. Signal processing is to extract the threshold echo data after the IQ data of the radar is processed by pulse pressure, interference suppression, Doppler filtering and threshold detection, and then according to the point trace. The extraction rules are used to detect and condense the echo data that belong to the same target in multiple range units and pitch / azimuth wave positions. Almost all modern radar systems use automatic track initiation and tracking processing algorithms. The effective extraction of target point traces and the effective suppression of false point traces are important prerequisites to ensure the stable output of real target tracks. [0003]...

AI Technical Summary

Problems solved by technology

However, both of these two methods can regulate the number of traces, but in the non-uniform and complex background, directly adjusting the detection threshold cannot take into account the suppression of false traces in the clutter area and the weak target detection in the non-clutter area. When the density of dot traces is high, direct dot trace filtering is performed to deal with clutter and dot trace recognition, which requires a large amount of calculation and is easy to miss the target.

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