By J. R. Guerci
Space-time adaptive processing (STAP) is a expertise for complex radar platforms that enables for major functionality improvements over traditional techniques. in response to a direction taught in undefined, govt and academia, it is a sensible creation to STAP recommendations and strategies, putting emphasis on implementation in real-world platforms. It addresses the wishes of radar engineers who're trying to observe potent STAP innovations to their structures, and will even be used as a reference by means of non-radar experts with an curiosity within the sign processing purposes of STAP. The authors target to provide an explanation for serious issues in a way that are meant to be comprehensible to someone with a simple historical past in radar and sign processing.
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Additional info for Space-Time Adaptive Processing for Radar (Artech House Radar Library)
59) for the ideal case (known-covariance). d. 49). Note that while there are certainly six large distinct eigenvalues, there is no definitive noise floor. 59). Unfortunately, except for the very strong jammer eigenvalues, the eigenvalues/vector pairs associated with the noise floor are not well estimated with only 2N samples. 9, is significant corruption of the adapted pattern sidelobes. 59) and set ˆ min = 2 (since the receiver noise floor is reasonably well-known in a calibrated radar), we should have a much better pattern.
Of IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Vol. 4, Seattle, WA, May 12–15, 1998, pp. 2505–2508. , ‘‘Circular Array STAP,’’ IEEE Trans. on Aerospace and Electronic Systems, Special Section on STAP, Vol. 36, No. 2, April 2000, pp. 510–517. 44 Space-Time Adaptive Processing for Radar  Guerci, J. , and J. S. Bergin, ‘‘Principal Components, Covariance Matrix Tapers, and the Subspace Leakage Problem,’’ IEEE Trans. on Aerospace and Electronic Systems, Vol.
There are basically two approaches to combat these effects: array tapering  and adaptive beamforming . 3 (for more details on antenna tapering, see ). 12) =C where A , B, C ∈ ރn × m, and the ij th element of C is given by c ij = a ij b ij . In words, given two conformal matrices of dimension n × m , the Hadamard product A ᭺ B = C is an n × m matrix whose elements are the pairwise products of the corresponding elements of A and B. 13) where * denotes conjugation without transposition, and [1 1 … 1] is a 1 × N row vector (Hadamard identity row vector) that acts as the summer operator.