Abstract
The chapter presents original methods and algorithms for adaptive spatial filtration. The methods target situation of uncertainty for parameters of both signals and interferences. The methods are implemented as both determinate and stochastic recurrent procedures . The recurrent algorithms are proposed using adaptive operators including constructing optimization tasks with either square or mixed constraints. The proposed approach is based on replacement of correlation matrices of input signals by corresponding consistent estimates. Also, the algorithms are presented with adaptation of operator’s structure to the real signal-interference environment. The results of simulation are shown conducted for determining the efficiency of proposed methods. The proposed algorithms are resistant to the value of input signal/noise relation for the wide class of signal-interference environments. They provide the values of output signal/(interference + noise) relation practically equal to the potentially reachable.
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Titarenko, L., Barkalov, A. (2013). Synthesis of ASF Algorithms for Not Exactly Known Parameters. In: Methods of Signal Processing for Adaptive Antenna Arrays. Signals and Communication Technology. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32132-0_7
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DOI: https://doi.org/10.1007/978-3-642-32132-0_7
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-32131-3
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