Olasilik hipotez yoǧunluǧu süzgeci kullanarak akustik sensörlerle kara araçlari takibi

Date

2012-04-20

Author

Özkan, Emre
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

30
views

0
downloads

In this paper, we explore the potential of networked microphone arrays for multiple target tracking. Tracking is accomplished by using the direction-of-arrival (DOA) estimates of multiple microphone arrays. Each microphone array obtains the DOA estimates by using the wideband extensions of the multiple signal classification (MUSIC) technique. Based on these DOA estimates, multi target tracking is done by using Probability hypothesis density (PHD) and cardinalized probability hypothesis density (CPHD) algorithms. The results show that the CPHD performs better than the PHD as it estimates the number of targets more accurately.

Subject Keywords

Multiple signal classification, Target tracking, Direction of arrival estimation, Reactive power, Wideband, Estimation

URI

https://hdl.handle.net/11511/43499

DOI

https://doi.org/10.1109/siu.2012.6204701

Collections

Department of Electrical and Electronics Engineering, Conference / Seminar

Suggestions

OpenMETU
Core

Ground multiple target tracking with a network of acoustic sensor arrays using PHD and CPHD filters Özkan, Emre; Orguner, Umut (null; 2011-07-08) In this paper, we explore the potential of networked microphone arrays for multiple target tracking. Tracking is accomplished by using the direction-of-arrival (DOA) estimates of multiple microphone arrays. Each microphone array obtains the DOA estimates by using the wideband extensions of the multiple signal classification (MUSIC) technique. Based on these DOA estimates, multi target tracking is done by using Probability hypothesis density (PHD) and cardinalized probability hypothesis density (CPHD) algori...
Target tracking and sensor placement for doppler–only measurements Ayazgök, Süleyman; Orguner, Umut; Department of Electrical and Electronics Engineering (2015) This thesis investigates the problems of target tracking and optimal sensor placement with Doppler-only measurements. First, a single point track initialization algorithm proposed in the literature is investigated for Doppler-only tracking. The initialization algorithm is based on separable least squares method and involves a grid-based optimization. Second, particle filters are considered for Doppler-only tracking and they are compared to an extended Kalman filter (EKF). It is shown that a classical bootst...
Occlusion-aware 3-D multiple object tracking for visual surveillance Topçu, Osman; Alatan, Abdullah Aydın; Ercan, Ali Özer; Department of Electrical and Electronics Engineering (2013) This thesis work presents an occlusion-aware particle filter framework for online tracking of multiple people with observations from multiple cameras with overlapping fields of view for surveillance applications. Surveillance problem involves inferring motives of people from their actions, deduced from their trajectories. Visual tracking is required to obtain these trajectories and it is a challenging problem due to motion model variations, size and illumination changes and especially occlusions between mov...
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-scan data association algorithm for multitarget tracking Ağırnas, Emre; Demirbaş, Kerim; Department of Electrical and Electronics Engineering (2004) Data association problem for multitarget tracking is determination of the relationship between targets and the incoming measurements from sensors of the target tracking system. Performance of a multitarget tracking system is strongly related to the chosen method for data association and target tracking algorithm. Incorrect data association effects state estimation of targets. In this thesis, we propose a new multi-scan data association algorithm for multitarget tracking systems. This algorithm was implement...

Citation Formats

E. Özkan and U. Orguner, “Olasilik hipotez yoǧunluǧu süzgeci kullanarak akustik sensörlerle kara araçlari takibi,” 2012, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/43499.