Target Track Prediction Method Based on Recurrent Neural Network

Abstract

The invention discloses a target track prediction method based on a cyclic neural network, which belongs to the field of radar target tracking and mainly solves the problems of simple model, low complexity, poor adaptability and inability to learn in the existing track prediction method. This method firstly collects the same type of radar measurement point track and tracking track data in multiple scenarios, and at the same time uses the cooperative target information receiving equipment to collect the cooperative target track, and removes and corrects the data to form the original track. data set. Then construct the target track prediction recurrent neural network, set the training sample feature vector, and generate the track training set. Finally, based on the cooperative track training set and the radar track training set, the target track prediction recurrent neural network is trained and optimized to generate a target track prediction method that matches the radar. This method can automatically train and generate a prediction algorithm, and has the advantages of wide application range, multiple adaptation scenarios, and good practical effect.

Description

Technical field[0001]The invention belongs to the field of radar target tracking, provides a target track prediction method, relates to the construction, training and generation of a cyclic neural network, and is suitable for a radar data processing system.Background technique[0002]Target tracking is the core key technology of radar data processing. It establishes the correspondence between each frame of radar measurement data and different real targets, and obtains the target's motion trajectory and motion parameters through filtering estimation, so as to achieve real-time continuous control of the target individual . Target tracking includes multiple technical links such as track initiation, track filtering, track prediction, and point-to-flight correlation. Track prediction is the key bottleneck link, which directly determines the effect of target tracking. If the trajectory prediction is inaccurate, it will affect the point-to-air correlation results, leading to point-to-air cor...

AI Technical Summary

Problems solved by technology

[0003] The purpose of the present invention is to propose a target track prediction method, aiming to solve the problems of the existing target track prediction method model simple, low complexity, poor adaptability and unable to learn

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