Decentralized array processing using the MODE algorithm
Circuits, Systems, and Signal Processing
Model-based processing in sensor arrays
Advances in spectrum analysis and array processing (vol. III)
Smart Antennas for Wireless Communications: IS-95 and Third Generation CDMA Applications
Smart Antennas for Wireless Communications: IS-95 and Third Generation CDMA Applications
Computationally efficient angle estimation for signals with knownwaveforms
IEEE Transactions on Signal Processing
Source localization with distributed sensor arrays and partial spatial coherence
IEEE Transactions on Signal Processing
A decoupled algorithm for geolocation of multiple emitters
Signal Processing
Cramér–Rao bound analysis of positioning approaches in GNSS receivers
IEEE Transactions on Signal Processing
Direct position determination in the presence of model errors---known waveforms
Digital Signal Processing
Direct positioning of stationary targets using MIMO radar
Signal Processing
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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, Cramér-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 waveforms.