Radar multi-target tracking PHD implementation method

Abstract

The invention discloses a radar multi-target tracking PHD implementation method, and the method specifically comprises the following steps: S1, calculating the state prediction estimation of each target at the k moment based on the states of a plurality of tracking targets at the k-1 moment; S2, converting the radar measurement data at the moment k into target state likelihood data under a Cartesian coordinate system; S3, performing product hybrid filtering on the Gaussian component predicted in the step 1 and target state likelihood data; S4, calculating Gaussian components and final weightsof all targets in the radar tracking area; S5, abandoning the Gaussian components of which the final weights are smaller than a pruning threshold value, and combining the Gaussian components of whichthe distribution distances are smaller than a combination threshold value; S6, taking the weight sum of all Gaussian components as the number of tracking targets, taking the mean value of the Gaussiancomponents with the weight greater than 0.5 as the target state, and iteratively carrying out the next round of filtering until the tracking is finished; the data fusion process is simple, the anti-clutter performance is excellent, the state estimation precision of the tracking target is high, and the target number estimation is accurate.

Description

technical field [0001] The invention belongs to the technical field of radar multi-target tracking, and in particular relates to a PHD realization method of radar multi-target tracking. Background technique [0002] With the rapid development of sensing technology and information fusion theory, radar tracking has been widely used in both military and civilian applications, such as air surveillance, missile defense, unmanned driving and weather monitoring, etc. However, with the complexity of the tracking environment Especially after entering the 21st century, new technologies such as stealth and electronic countermeasures are becoming more and more perfect, and the conventional single-target radar tracking method is no longer enough to deal with these problems. [0003] In the 1950s, Multiple Target Tracking (MTT) was first proposed. In the past 60 years, MTT has achieved many remarkable results in the field of radar tracking. When the radar tracks multiple targets, the main...

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Problems solved by technology

[0005] However, as an emerging filtering technology, PHD has many shortcomings in practical applications, such as difficulty in implementation, poor stability, and inability to directly deal with nonlinear systems; when tracking and monitoring multiple targets, the radar will be interfered by clutter and produce false Measurement, the measurement data is the straight-line distance between the radar and the target, the tilt angle and the pitch angle between the radar and the target, the measurement data and the target position in the Cartesian coordinate system constitute a set of nonlinear functions. The filtering algorithm is combined with PHD, which has a large amount of calculation, and the estimation accuracy of the number of targets is low, and the target tracking trajectory is unstable, especially when the number of targets in the tracking area is large, the radar tracking effect is worse

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