A Multi-Sensor Multi-Target Joint Detection, Tracking and Classification Method

Abstract

The invention provides a multi-sensor multi-target joint detection, tracking and classification method, which is characterized in that the method comprises the following steps: S1, defining a new Bayesian risk given the initial value of the multi-target state; S2, predicting the multi-objective state under the condition of the category hypothesis in the category hypothesis set to obtain the priorstate distribution of the multi-objective; 3, under the condition of a class decision set, calculating a multi-objective posterior density at the time k to obtain a posterior multi-objective state distribution; S4, calculating multi-target detection loss, state estimation loss and classification loss under different decision conditions; S5: according to the detection loss, the state estimation loss and the classification loss, the multi-objective estimation and the classification optimal solution are obtained based on the minimum Bayesian risk criterion. This method is easy to implement and provides important technical support for multi-sensor networking environment sensing system.

Description

technical field [0001] The invention relates to the technical field of sensor target detection, in particular to a multi-sensor multi-target joint detection, tracking and classification method. Background technique [0002] Multi-sensor multi-target joint detection, tracking and classification is an important and complex problem to be solved in battlefield environment monitoring. This problem solves the detection, tracking and identification of military targets (ships, aircraft, missiles) in the surveillance area. In practical applications, networking of multiple (heterogeneous) sensors is a common means. The system generally includes various types of sensors, such as radar (Radar), infrared (IR), electronic support (ESM), identification friend or foe (IFF), etc., and the use of measurement complementarity and information fusion between sensors can improve target Comprehensive discovery probability, tracking accuracy, and recognition accuracy. [0003] To solve this probl...

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Problems solved by technology

[0005] The purpose of the present invention is to provide a multi-sensor multi-target joint detection, tracking and classification method to solve the existing method because the correlation between decision-making and estimation cannot be obtained and the joint optimal solution cannot be given. Questions about explicit decisions and corresponding estimated outcomes

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