A tracker-aware detector threshold optimization formulation for tracking maneuvering targets in clutter

Date

2011-09-01

Author

Aslan, Murat Samil
Saranlı, Afşar

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

237
views

0
downloads

In this paper, we consider a tracker-aware radar detector threshold optimization formulation for tracking maneuvering targets in clutter. The formulation results in an online method with improved transient performance. In our earlier works, the problem was considered in the context of the probabilistic data association filter (PDAF) for non-maneuvering targets. In the present study, we extend the ideas in the PDAF formulation to the multiple model (MM) filtering structures which use PDAFs as modules. Although our results are general for the MM filters, our simulation experiments apply the proposed solution in particular for the interacting multiple model PDAF (IMM-PDAF) case. It is demonstrated that the suggested formulation and the resulting optimization method exhibits notable improvement in transient performance in the form of track loss immunity. We believe the method is promising as a detector-tracker jointly-optimal filter for the IMM-PDAF structure for tracking maneuvering targets in clutter.

Subject Keywords

Control and Systems Engineering, Signal Processing, Electrical and Electronic Engineering, Software, Computer Vision and Pattern Recognition

URI

https://hdl.handle.net/11511/41542

Journal

SIGNAL PROCESSING

DOI

https://doi.org/10.1016/j.sigpro.2011.04.004

Collections

Department of Electrical and Electronics Engineering, Article

Suggestions

OpenMETU
Core

Extended Target Tracking Using Polynomials With Applications to Road-Map Estimation Lundquist, Christian; Orguner, Umut; Gustafsson, Fredrik (Institute of Electrical and Electronics Engineers (IEEE), 2011-01-01) This paper presents an extended target tracking framework which uses polynomials in order to model extended objects in the scene of interest from imagery sensor data. State-space models are proposed for the extended objects which enables the use of Kalman filters in tracking. Different methodologies of designing measurement equations are investigated. A general target tracking algorithm that utilizes a specific data association method for the extended targets is presented. The overall algorithm must always ...
New method for the fusion of complementary information from infrared and visual images for object detection Ulusoy, İlkay (Institution of Engineering and Technology (IET), 2011-02-01) Visual and infrared cameras have complementary properties and using them together may increase the performance of object detection applications. Although the fusion of visual and infrared information results in a better recall rate than using only one of those domains, there is always a decrease in the precision rate whereas the infrared domain on its own always has higher precision. Thus, the fusion of these domains is meaningful only for a better recall rate, which means that more foreground pixels are de...
An Extended Target CPHD Filter and a Gamma Gaussian Inverse Wishart Implementation Lundquist, Christian; Granstrom, Karl; Orguner, Umut (Institute of Electrical and Electronics Engineers (IEEE), 2013-06-01) This paper presents a cardinalized probability hypothesis density (CPHD) filter for extended targets that can result in multiple measurements at each scan. The probability hypothesis density (PHD) filter for such targets has been derived by Mahler, and different implementations have been proposed recently. To achieve better estimation performance this work relaxes the Poisson assumptions of the extended target PHD filter in target and measurement numbers. A gamma Gaussian inverse Wishart mixture implementat...
Making linear prediction perform like maximum likelihood in Gaussian autoregressive model parameter estimation Candan, Çağatay (Elsevier BV, 2020-01-01) A two-stage method for the parameter estimation of Gaussian autoregressive models is proposed. The proposed first stage is an improved version of the conventional forward-backward prediction method and can be interpreted as its weighted version with the weights derived from the arithmetic mean of the log-likelihood functions for different conditioning cases. The weighted version is observed to perform better than the conventional forward-backward prediction method and other linear prediction based methods (...
Comments on "Detection of signals of unknown duration by multiple energy detectors" SİPAHİGİL, OKTAY; Çiloğlu, Tolga (Elsevier BV, 2014-01-01) In the 2010 paper entitled "Detection of signals of unknown duration by multiple energy detectors", a procedure to detect signals of unknown duration under Gaussian noise has been proposed and probability of detection and probability of false alarm expressions have been derived. This note indicates an error made at the beginning of these derivations.

Citation Formats

M. S. Aslan and A. Saranlı, “A tracker-aware detector threshold optimization formulation for tracking maneuvering targets in clutter,” SIGNAL PROCESSING, pp. 2213–2221, 2011, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/41542.