Tracking of manoeuvring targets using fuzzy information fusion filter. (3rd April 2018)

• Record Type: Journal Article
• Authors: George, Deepa Elizabeth; Unnikrishnan, A.
• Is Part Of: International journal of image and data fusion. Volume 9:Number 2(2018)
• Page Start: 115
• Page End: 130
• Publication Date: 2018-04-03
• Subjects: Information filter -- bearing angle -- multi-sensor data fusion -- fuzzy function -- range rate; Image processing -- Periodicals; Multisensor data fusion -- Periodicals; Multisensor data fusion; Periodicals; 621.36705
• DOI: 10.1080/19479832.2017.1342708
• Languages: English
• ISSNs: 1947-9832

Abstract

ABSTRACT: The paper discusses the tracking of a manoeuvring target using fuzzy information fusion filters (FIFFs), based on bearing only measurements received from multiple sensors. While a number of tracking filters including the Kalman filters have been proposed and demonstrated successfully for tracking, the information filter has been reported to be capable of estimating the state of a target even without an initial estimate. However, the estimate is often seen to diverge after a short period. A FIFF has been shown to track small manoeuvres in target following a constant velocity model but is not effective when the target switches to a coordinated turn model. In this paper, the idea of using the FIFF for tracking manoeuvring target is proposed and demonstrated. The filter uses only the bearing measurements in tracking the target and also for detecting the manoeuvre. Using an adaptive turn rate model, the turning rate of the moving target is estimated from the range rate. Here, the range rate is also computed directly from bearing measurements. The detection of the onset of manoeuvre is on the basis of consistent change in the turning rate of the target. A number of different scenarios involving manoeuvring targets are given to demonstrate the efficacy of this approach.