Spatial evolutionary spectrum for DOA estimation and blind signal separation

A. Salim Kayhan; Moeness G. Amin

doi:10.1117/12.367664

2 November 1999 Spatial evolutionary spectrum for DOA estimation and blind signal separation

A. Salim Kayhan, Moeness G. Amin

Proceedings Volume 3807, Advanced Signal Processing Algorithms, Architectures, and Implementations IX; (1999) https://doi.org/10.1117/12.367664
Event: SPIE's International Symposium on Optical Science, Engineering, and Instrumentation, 1999, Denver, CO, United States

Abstract

In this paper, we use the concept of evolutionary spectrum to solve key problems in array processing. We present Cross-power Evolutionary Periodogram for direction finding and blind separation of nonstationary signals. We model nonstationary signals received by each sensor in the array as a sum of complex sinusoids with time-varying amplitudes. These amplitudes carry information about the direction of arrival which may also be time-varying. We first estimate the time-varying amplitudes, then use the results for the estimation of evolutionary cross-power distributions of the sensor data. Next, using cross-power estimates at time-frequency samples of interest, we estimate the directions of arrival using one of the existing high resolution direction finding methods. If the directions are time-varying, we select time-frequency points around the time of interest. By carrying out the estimation at different times, we obtain the directions as a function of time. If the sources are stationary, then we can use all time-frequency points of interest for the estimation of fixed directions. We also use whitening and subspace methods to find the mixing matrix and separate the signals received by the array. Simulation examples illustrating the performances of the proposed algorithms are presented.

Citation Download Citation

A. Salim Kayhan and Moeness G. Amin "Spatial evolutionary spectrum for DOA estimation and blind signal separation", Proc. SPIE 3807, Advanced Signal Processing Algorithms, Architectures, and Implementations IX, (2 November 1999); https://doi.org/10.1117/12.367664

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KEYWORDS

Sensors

Time-frequency analysis

Matrices

Signal to noise ratio

Statistical analysis

Error analysis

Interference (communication)

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