Method for tracking extended target by multiple sensors with partially overlapped monitoring areas

Abstract

The invention discloses a method for tracking an extended target by multiple sensors with partially overlapped monitoring areas. A Gaussian component which is used when a current measurement set is subjected to wave filtering serves as a Gaussian component which is predicted at a current moment rather than a Gaussian component after the measurement of any one sensor is updated, so that the results of the sensors after wave filtering updating are mutually independent; after the measurements of all sensors participate in the wave filtering updating, Gaussian items in the results of all the sensors are judged: if a component representing a target position in the Gaussian item estimated by the sensor falls into an overlapping area, the weight value of the component is subjected to averaging optimization treatment; finally, the weight values, the average values and the covariances of the Gaussian items estimated by all the sensors are combined into one Gaussian component which serves as the Gaussian component predicted at a next moment. By using the method for tracking the extended target by the multiple sensors with the partially overlapped monitoring areas, which is provided by the invention, the problem that a target quantity is over-estimated due to the overlapping areas and the problem that measurement information is seriously lost due to non-overlapping areas are solved.

Description

technical field [0001] The invention belongs to the technical field of target tracking and target positioning methods, and relates to a target tracking method in a multi-sensor environment, in particular to an extended target tracking method in which multi-sensor presence monitoring areas partially overlap. Background technique [0002] With the continuous improvement of the accuracy of modern sensors, the sensor not only receives one measurement when monitoring a single target, but more often multiple measurements generated by one target can be monitored, which can generate more than one An object that measures information is called an extended object. [0003] The extended target tracking algorithm under multi-sensor conditions aims to select the appropriate algorithm to fuse the measurement information received by each sensor. After the fused information is filtered, it can more accurately reflect the real state of the group target. In the process of fusion, multiple sen...

AI Technical Summary

Problems solved by technology

The multi-sensor fusion algorithm disclosed above can be directly applied to the extended target tracking process. However, the existing multi-sensor fusion algorithms all assume that the sensor monitoring areas do not overlap, that is, each sensor has its own independent monitoring area , do not interfere with each other

In an actual multi-sensor environment, the monitoring areas of the sensors often overlap with different situations.

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