Multi-target track-before-detect method based on probability hypothesis density filtering

A probability hypothesis density and multi-target technology, which is applied in the field of multi-target tracking before detection based on probability hypothesis density filtering, can solve the problems of large amount of calculation, poor real-time performance, missed detection or wrong detection, etc.
CN105975772AActive Publication Date: 2016-09-28ZHEJIANG UNIV
2 Cites 8 Cited by

Patent Information

Authority / Receiving Office
CN Β· China
Current Assignee / Owner
ZHEJIANG UNIV
Publication Date
2016-09-28

Smart Images

  • Figure 1
    Figure 1
  • Figure 2
    Figure 2
  • Figure 3
    Figure 3
Patent Text Reader

Abstract

The invention discloses a multi-target track-before-detect method based on probability hypothesis density filtering. The method deeply analyzes the problem of a traditional method and points out the essential reason of the problem of the traditional method that the traditional method considers that one target influences the observation of a whole area and also considers that the number of each frame of false alarm can be approximated into one constant value, i.e. the traditional method does not comply with two pieces of basic hypothesis for realizing PHD (Probability Hypothesis Density) filtering: firstly, one target only can generate one observation, and secondly, the number of each frame of false alarm must submit to Poisson distribution on an aspect of time. In order to solve the problems, the invention puts forward the multi-target track-before-detect method based on the probability hypothesis density filtering, can improve the accuracy of target number estimation, enhances detection and tracking performance, and also achieves an effect on lowering a calculated amount.
Need to check novelty before this filing date? Find Prior Art

Description

technical field

[0001] The invention belongs to the technical field of target detection and tracking, and in particular relates to a multi-target tracking method before detection based on probability hypothesis density filtering. Background technique

[0002] In the current research on weak target detection and tracking methods in the strong clutter background, the Track Before Detect (TBD) method is unanimously believed by domestic and foreign scholars that it can greatly improve the detection and tracking performance of weak targets. The main feature of the TBD method is that there is no threshold for single-frame observation. Since it takes the entire original signal as the observation input, it retains the target information to the greatest extent and avoids the loss of single-frame detection. Therefore, it can improve the detection and tracking performance of faint targets. Probability Hypothesis Density (PHD) is a filter based on the framework of random set theory. It...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More