@inproceedings{6ca108b5e2a94fb781737d7e7ef16e1a,
title = "Improved Model-Based Rao and Wald Test for Adaptive Range-Spread Target Detection",
abstract = "This article addresses the problem of the detection of range-spread targets in the presence of Gaussian disturbance which are in possession of unidentified covariance matrices. The detectors have been derived by resorting to a design composed of two steps. Based on the Rao test and Wald test, the corresponding strategies of detection have been respectively derived very firstly, assuming the expression of disturbance covariance matrix has been obtained. Afterwards, the unknown parameters in the detectors have been estimated on the basis of both the primary and the training data, utilizing the autoregressive property of the disturbance. A remarkable characteristic of the Rao and Wald detectors is they both asymptotically attain constant false alarm rate(CFAR) in respect of the disturbance covariance matrix. Finally, we completed a performance assessment by utilizing the simulated data, and the result demonstrated the effectiveness of the existing proposals compared with the detectors previously proposed.",
keywords = "Rao test, Wald test, autoregressive, range-spread target",
author = "Jiabao Liu and Haoxuan Xu and Zihao Chen and Meiguo Gao",
note = "Publisher Copyright: {\textcopyright} 2021 IEEE.; 4th IEEE International Conference on Electronics Technology, ICET 2021 ; Conference date: 07-05-2021 Through 10-05-2021",
year = "2021",
month = may,
day = "7",
doi = "10.1109/ICET51757.2021.9450915",
language = "English",
series = "2021 IEEE 4th International Conference on Electronics Technology, ICET 2021",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1223--1228",
booktitle = "2021 IEEE 4th International Conference on Electronics Technology, ICET 2021",
address = "United States",
}