Radar Selection Method Based on an Improved Information Filter in the LPI Radar Network

In order to save the radar resources and obtain the better low probability intercept ability in the network, a novel radar selection method for target tracking based on improved interacting multiple model information filtering (IMM-IF) is presented. Firstly, the relationship model between radar reso...

Full description

Saved in:
Bibliographic Details
Published in:International journal of antennas and propagation 2018-01, Vol.2018 (2018), p.1-6
Main Authors: Yang, Yi, Xie, Zhibin, Zhang, Bing, Zhang, Zhen-kai
Format: Article
Language:English
Subjects:
Algorithms
Computer simulation
Covariance
Interactive multiple model tracking
Kalman filters
Mathematical models
Model accuracy
Noise
Predictions
Probability
Radar networks
Radar systems
Radar tracking
Scheduling
Sensors
Signal processing
Surveillance
Weight
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:In order to save the radar resources and obtain the better low probability intercept ability in the network, a novel radar selection method for target tracking based on improved interacting multiple model information filtering (IMM-IF) is presented. Firstly, the relationship model between radar resource and tracking accuracy is built, and the IMM-IF method is presented. Then, the information gain of every radar is predicted according to the IMM-IF, and the radars with larger information gain are selected to track target. Finally, the weight parameters for the tracking fusion are designed after the error covariance prediction of every working radar, in order to improve the IMM-IF. Simulation results show that the proposed algorithm not only saves much more radar resources than other methods but also has excellent tracking accuracy.
ISSN:1687-5869
1687-5877
DOI:10.1155/2018/6104849