Multi-source data fusion method for low-speed small target detection system

Abstract

The invention relates to a multi-source data fusion method for a low-speed small target detection system, and belongs to the technical field of radar information detection. The multi-source data fusion method includes six implementation steps, aiming at low, slow and small target track characteristics, calculates the single-source track quality data in real time, distributes a fusion weight in a self-adaptive manner according to the track quality data, is high in adaptability to complex and changing environment backgrounds, can utilize multi-radar cooperative detection to the maximum extent, can bring the advantages of multi-sensor networking detection into full play, can effectively improve the detection precision and the detection stability of low, slow and small target tracks, can savenetworking resources, and can improve the environment adaptability of the multi-source information fusion method. The multi-source data fusion method solves the problems that a weighted average fusionmethod is adopted in an existing multi-sensor multi-source information fusion method, and initially gives a weight coefficient, so that the method is difficult to adapt to the influence of environmental interference in low, slow and small target detection, and the fusion result precision is not high due to unreasonable setting of the weight coefficient, and networking resources are wasted.

Description

technical field [0001] The invention relates to a multi-source data fusion method for a low-slow and small-target detection system, which belongs to the technical field of radar information detection. Background technique [0002] Common low-slow and small targets include multi-rotor drones, aerial photography balloons, and powered delta wings. The radar scattering area of ​​low, slow and small targets is small, the flying altitude is low, the speed is slow, and the Doppler frequency shift is not obvious. In addition, the use environment is complex and the background interference is large, and the air force radar equipment cannot cover it. recognized problem. It is an effective way to detect slow and small targets through a multi-sensor network, but how to maximize the advantages of each sensor and obtain better detection accuracy than a single sensor is an urgent problem to be solved by multi-sensor information fusion. At present, the multi-sensor information fusion metho...

AI Technical Summary

Problems solved by technology

At present, the multi-sensor information fusion method usually adopts the weighted average fusion method, and the weight coefficient is initially given. This kind of fixed weight coefficient is difficult to adapt to the influence of environmental interference in the detection of low-speed and small targets, and it is easy to appear due to the weight coefficient Unreasonable settings lead to low accuracy of fusion results and waste of networking resources, making it impossible to make the most of the advantages of multi-radar equipment networking and collaborative detection to achieve efficient detection and identification of low-slow and small targets

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