Weighted constraint composite filtering method based on unmanned aerial vehicle obstacle avoidance millimeter wave radar

Abstract

The invention discloses a weighted constraint composite filtering method based on an unmanned aerial vehicle obstacle avoidance millimeter wave radar. The method comprises the following steps: acquiring an original echo signal; performing down-conversion processing; signal pulse compression; a prefilter and a postfilter are used for weighted constraint composite filtering, the prefilter uses a sidelobe cancellation algorithm to construct a covariance matrix characteristic threshold signal subspace, and weighted iteration is carried out on the characteristic signal subspace of the covariance matrix characteristic threshold signal subspace; the post-filter performs least square recursion on the inverse of the autocorrelation matrix of the input signal, and introduces genetic factors in the recursion process to reduce the influence of old data on new data; performing CFAR detection in the distance direction; and target tracking and identification. According to the method, recursive estimation updating is performed on the input signal, the convergence speed is high, and the filtering effect is very obvious; an algorithm structure is formed by compounding a prefilter and a post-filter, and the post-filter can effectively solve the problem that an enhanced signal output by the prefilter still has excessive noise residues.

Description

technical field [0001] The invention belongs to the technical field of millimeter-wave radar, and in particular relates to a weighted and constrained compound filtering method based on a UAV obstacle avoidance millimeter-wave radar. Background technique [0002] UAV obstacle avoidance radar can send and receive electromagnetic waves and process echo signals to determine whether there are obstacles ahead, feedback the relative distance, speed, azimuth and other information between obstacles and radar, and guide UAVs and other radar carriers to avoid obstacles autonomously , to ensure its safe operation. However, the weather and environment in which UAVs actually operate are complex and changeable. Even if an obstacle avoidance radar is installed, it is easy to hit obstacles with weak energy such as thin wires and dead branches, causing the aircraft to explode. After analyzing a large number of UAV obstacle avoidance radar measured data, it is concluded that the noise floor e...

AI Technical Summary

Problems solved by technology

However, the weather and environment of the actual operation of the UAV are complex and changeable. Even if the obstacle avoidance radar is installed, it is easy to collide with weak energy obstacles such as thin wires and dead branches, causing the aircraft to explode.

After a large number of UAV obstacle avoidance radar measured data analysis, it is concluded that the background noise energy is greatly increased due to the interference of environmental clutter, which leads to the submersion of weak target echo energy, so that the radar detection algorithm cannot track the target, resulting in the failure of the obstacle avoidance radar.

Images