A multi-target detection and tracking method under the condition of low observable and high clutter

A multi-target, high-complexity technology, applied in the extended field of maximum likelihood-probability multi-hypothesis tracking, it can solve problems such as inability to accumulate target information, false target state parameter estimates, and other targets being difficult to find.

Inactive Publication Date: 2019-01-11
UNIV OF ELECTRONICS SCI & TECH OF CHINA
View PDF5 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, the relationship between these measurements and the observed function before the target state is different, and the LLR calculated with a fixed likelihood function not only cannot accumulate target information, but also forms false target state parameter estimates
In addition, the existing basic ML-PMHT algorithm uses sequence detection for multiple targets. When the targets are close to each other, one target is searched, and other targets are not easy to be found.

Method used

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
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • A multi-target detection and tracking method under the condition of low observable and high clutter
  • A multi-target detection and tracking method under the condition of low observable and high clutter
  • A multi-target detection and tracking method under the condition of low observable and high clutter

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0065] In order to make the purpose, technical solution and advantages of the present invention clearer, the specific implementation manners of the present invention will be further described in detail below.

[0066] (1) Initialize the background parameters.

[0067] 1a. In the over-the-horizon radar application scenario, the receiver sensor is fixed at [0km, 0km] to collect the signal reflected by the ionosphere, and the transmitter sensor is fixed at [100km, 0km]. Suppose there are two ideal ionospheres E and F such as figure 1 As shown, they correspond to two fixed heights h E = 100km and h F = 220km, then the signal has four propagation paths of EE, EF, FE and FF from the transmitter sensor to the target and then to the receiver sensor. A total of 35 sampling moments were observed in this scene. The sliding window of the JML-MP-PMHT algorithm contains 10 sampling moments, that is, 10 frames of data, and each time the sliding window is executed, the sliding window slide...

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

PUM

No PUM Login to view more

Abstract

The invention discloses a multi-target detection and tracking method under the condition of low observability and high clutter, and belongs to the technical field of radar and sonar. The idea of ​​the present invention is to consider multiple measurements arriving at the receiver through different propagation paths as possible target measurements when dealing with the correlation problem between objects and measurements, and compare these measurements with known The multi-path measurement function is correctly correlated, so as to obtain the accumulation of target information and enhance the target detection ability; then the target is tracked by means of a sliding window. The present invention utilizes the target information that arrives at the sensor through different channels, and correctly correlates these measurement information with known multipath measurement functions, thereby obtaining the accumulation of target information and enhancing the target at low observable and high clutter levels. The detection ability in the environment can effectively reduce the influence between adjacent targets.

Description

technical field [0001] The invention belongs to the technical field of radar and sonar, and mainly relates to an extension method of maximum likelihood-probability multiple hypothesis tracking (ML-PMHT). technical background [0002] Target tracking technology is widely used in various fields, especially radar (sonar) signal system. The target tracking technology is divided into two categories: track after detection (TAD) and track before detection (TBD). In comparison, the calculation amount of TAD algorithm is low, which is conducive to real-time implementation, but because the TAD algorithm relies on the front-end signal processor to Target detection, tracking performance is not ideal in the case of low signal-to-noise ratio (SNR). Because the TBD algorithm adds target detection while tracking, it has a strong tracking ability for the target under low signal-to-noise ratio, but the application of the TBD algorithm in engineering is subject to many restrictions due to the...

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

Application Information

Patent Timeline
no application Login to view more
Patent Type & Authority Patents(China)
IPC IPC(8): G01S13/72G01S15/66G01S7/292G01S7/35G01S7/527G01S7/536
CPCG01S7/2927G01S7/354G01S7/527G01S7/536G01S13/726G01S15/66
Inventor 唐续吴骐朱士强
Owner UNIV OF ELECTRONICS SCI & TECH OF CHINA
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products