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Distributed Target Detection Using Samples Filtered with Normalized Conjugate Signal Steering Vector

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Abstract

This paper studied the problem of adaptive detection of distributed targets in colored noise with unknown covariance matrix (CM), for the case where limited noise-only (training) data are available to estimate this CM. We first filter the test and training data with the normalized conjugate signal steering vector which is matched to the target signal, to preserve the signal power while suppressing the noise power; second, we derive the generalized likelihood ratio test. The new detector has the desired constant false alarm rate feature against the noise CM; it needs less training data, has a lower computational complexity and performs better (more robust) for matched (mismatched) signals, when compared with its natural counterparts.

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Notes

  1. The one-step (OS) design strategy means that all the unknown parameters are replaced by their estimates within one step.

  2. The test data are sampled from the cells under test (CUTs); they contain only Gaussian noise under the null hypothesis, and they contain Gaussian noise plus useful signal under the alternative hypothesis.

  3. The training data are sampled from the cells adjacent to the CUTs; they contain only independent and identically distributed Gaussian noise. The training data are mainly used to estimate the noise covariance matrix (NCM) of the test data.

  4. The homogeneous environment means that the test and training data have the same NCM.

  5. The two-step (TS) design strategy contains two steps: First, the NCM is assumed to be known and the test statistic is derived; then, the NCM is replaced by its estimate which involves the training data alone.

  6. This selective means that a detector is sensitive to the mismatched signals.

  7. The quasi-whitening subspace means that the subspace is not whitened by the actual NCM but by the estimate of the NCM. This estimate is calculated from the training data alone.

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  1. School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, 611731, Sichuan, China

    Zuozhen Wang

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Wang, Z. Distributed Target Detection Using Samples Filtered with Normalized Conjugate Signal Steering Vector. Circuits Syst Signal Process 39, 4762–4774 (2020). https://doi.org/10.1007/s00034-020-01389-8

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  • DOI: https://doi.org/10.1007/s00034-020-01389-8

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