Navigation radar target detection and tracking algorithm based on USV
A target detection and tracking method for navigation radar is proposed to improve the detection ability of unmanned surface vessel for surface targets.This method addresses the problems of fragmented regions in the radar echo map and large errors in tracking moving targets during the process of environmental perception using navigation radar.Firstly,the original echo image of the radar is analyzed and corrected to obtain the required echo image.Secondly,based on image connectivity,a self-adaptive threshold segmentation Hausdorff matching algorithm is designed to match the echo map and the map,distinguishing the echoes belonging to the target and the land.Thirdly,the target matching is performed on the continuous two frames of radar echoes.Finally,the empirical model decomposition(EMD)algorithm of the predictive sequence model is added to optimize the detection and tracking results,and improve the accuracy of obtaining target information.The results of experimental verification show that for surface targets with a relative motion speed of less than 30 knots within 1 km,the distance error is less than 2％,the target detection probability increases by 6.5％,the speed error is less than 6％,and the heading error is less than 6° using this method.The overall performance is better than that of the detection and tracking methods commonly used in engineering.
environmental perceptionnavigation radarconnectivity algorithmmap matchingempirical model decomposition(EMD)algorithm
万方数据
维普
