tailieunhanh - Báo cáo hóa học: " Direct Position Determination of Multiple Radio Signals"

Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Direct Position Determination of Multiple Radio Signals | EURASIP Journal on Applied Signal Processing 2005 1 37-49 2005 Hindawi Publishing Corporation Direct Position Determination of Multiple Radio Signals Anthony J. Weiss Department of Electrical Engineering-Systems Tel Aviv University Tel Aviv 69978 Israel Email ajw@ Alon Amar Department of Electrical Engineering-Systems Tel Aviv University Tel Aviv 69978 Israel Email amar@ Received 25 December 2003 Revised 8 June 2004 The most common methods for position determination of radio signal emitters such as communications or radar transmitters are based on measuring a specified parameter such as angle of arrival AOA or time of arrival TOA of the signal. The measured parameters are then used to estimate the transmitter s location. Since the measurements are done at each base station independently without using the constraint that the AOA TOA estimates at different base stations should correspond to the same transmitter s location this is a suboptimal location determination technique. Further if the number of array elements at each base station is M and the signal waveforms are unknown the number of cochannel simultaneous transmitters that can be localized by AOA is limited to M - 1. Also most AOA algorithms fail when the sources are not well angularly separated. We propose a technique that uses exactly the same data as the common AOA methods but the position determination is direct. The proposed method can handle more than M - 1 cochannel simultaneous signals. Although there are many stray parameters only a two-dimensional search is required for a planar geometry. The technique provides a natural solution to the measurements sources association problem that is encountered in AOA-based location systems. In addition to new algorithms we provide analytical performance analysis Cramer-Rao bounds and Monte Carlo simulations. We demonstrate that the proposed approach frequently outperforms the traditional AOA methods for unknown as well as known signal .

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