Research on DOA Estimation and Tracking for Multiple Targets
| Autor: | Sheng-Yun Hou, 何昇運 |
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| Rok vydání: | 2010 |
| Druh dokumentu: | 學位論文 ; thesis |
| Popis: | 98 In this dissertation, we are aimed at developing novel angle tracking algorithms. First of all, three novel angle tracking algorithms are proposed for tracking multiple targets using an array of sensors with known locations. The first algorithm, called EKF-PAT, is a predictive angle tracking (PAT) method based on the extended Kalman filter (EKF). The EKF-PAT algorithm provides lower computational complexity and also improves the tracking performance especially at lower number of snapshots. Combined with the coherent signal-subspace (CSS) method, the EKF-PAT algorithm can track the direction-of-arrival angles (DOAs) of wideband sources. In addition, we also extend the EKF-PAT algorithm to track the range, azimuth, and elevation of each narrowband source in 3-D space. The second algorithm, called EKPF-AT, is an angle tracking algorithm based on the extended Kalman particle filter (EKPF). This algorithm is capable of determining DOA angles using a single snapshot of data during the interval between each time step. The EKPF combines particle filtering (PF) with the extended Kalman filter (EKF) in order to prevent sample impoverishment during its resampling process. The third algorithm, called RKF-AT, is an angle tracking algorithm based on the Kalman filter and a robust decision mechanism. The RKF-AT algorithm is intended to improve tracking success rates of other existing algorithms for the case of multiple snapshots of data within each time increment. In the RKF-AT algorithm, a robust decision mechanism is proposed and incorporated into the Kalman filter, leading to a much better tracking success rate. Through extensive computer simulations, performances of our three proposed algorithms are demonstrated and compared with the other existing ones. Next, we propose a design and implementation methodology for an acoustic DOA estimator which is based on TMS320VC33 digital signal processor (DSP) chip. In order to validate its feasibility, a DOA estimation algorithm, installed in PC and the DSP chip respectively, is used in conjunction with the relevant hardware instruments to perform DOA estimation experiments in the shallow water of the Bi-Sha fishery harbor. |
| Databáze: | Networked Digital Library of Theses & Dissertations |
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