Centralized Target Tracking with Propagation Delayed Measurements

Date

2013-07-12

Author

MEHMETCIK, Erdal
Orguner, Umut

Metadata

Show full item record

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

Item Usage Stats

17
views

0
downloads

In this paper, we investigate the multisensor target tracking problem in environments where the signal propagation delays between the target and the sensors are not negligible. Based on a previously proposed efficient method to solve the implicit equations imposed by the target motion model and the physics rules governing the signal propagation delays, a particle filter is developed to perform multisensor target tracking while compensating for the propagation delays. As opposed to the existing approach in the literature, a centralized tracking architecture, which brings up significant challenges into the problem, is considered. The performance of the new approach is illustrated on an example scenario where a target with a coordinated-turn motion is to be tracked with two bearing-only sensors.

Subject Keywords

Centralized estimation, Particle filtering, Target tracking, State estimation, Propagation delay, Multiple sensors

URI

https://hdl.handle.net/11511/53958

Collections

Department of Electrical and Electronics Engineering, Conference / Seminar

Suggestions

OpenMETU
Core

Distributed Target Tracking with Propagation Delayed Measurements Orguner, Umut (2009-07-09) This paper presents a framework for making distributed target tracking under significant signal propagation delays between the target and the sensors. Each sensor considered makes estimation using its own measurements compensating for the involved signal propagation delay using a deterministic sampling based algorithm proposed previously. Since the individual sensor readings might not be enough to localize the target, the sensors have to share their estimates with each other at specific time instants and co...
Multi-Ellipsoidal Extended Target Tracking Using Sequential Monte Carlo Kara, Süleyman Fatih; Özkan, Emre (2018-07-10) In this paper, we consider the problem of extended target tracking, where the target extent cannot be represented by a single ellipse accurately. We model the target extent with multiple ellipses and solve the resulting inference problem, which involves data association between the measurements and sub-objects. We cast the inference problem into sequential Monte Carlo (SMC) framework and propose a simplified approach for the solution. Furthermore, we make use of the Rao-Blackwellization, aka marginalization...
Multi-dimensional hough transform based on unscented transform as a method of track-before-detect / Şahin, Gözde; Demirekler, Mübeccel; Department of Electrical and Electronics Engineering (2014) Track-Before-Detect (TBD) is the problem where target state estimation and detection occur simultaneously, and is a suitable method for the detection of low-SNR targets in unthresholded sensor data. In this thesis, a new Multi-Dimensional Hough Transform (MHT) technique based on Unscented Transform is proposed for the detection of dim targets in radar data. MHT is a TBD method that fuses Hough Transform results obtained on (x-t), (y-t) and (x-y) domains in order to detect a constant velocity target. The pro...
A Variational Measurement Update for Extended Target Tracking With Random Matrices Orguner, Umut (2012-07-01) This correspondence proposes a new measurement update for extended target tracking under measurement noise when the target extent is modeled by random matrices. Compared to the previous measurement update developed by Feldmann et al., this work follows a more rigorous path to derive an approximate measurement update using the analytical techniques of variational Bayesian inference. The resulting measurement update, though computationally more expensive, is shown via simulations to be better than the earlier...
The MUSIC algorithm-based electromagnetic target classification for isolated targets from incomplete frequency domain data Secmen, Mustafa; Sayan, Gönül (2007-06-15) This paper investigates the performance of a new electromagnetic target classification method to recognize isolated targets in the presence of scattered frequency domain data which may be severely incomplete at low frequencies. The suggested method utilizes multiple signal classification (MUSIC) algorithm to construct approximate pole location maps of the targets without determining the exact pole values. In this work, this method is validated for small-scale aircraft targets modeled by thin, conducting wir...

Citation Formats

E. MEHMETCIK and U. Orguner, “Centralized Target Tracking with Propagation Delayed Measurements,” 2013, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/53958.