TY - GEN
T1 - An Improved Model-Based Wald Detector for Range-Spread Targets in Heterogeneous Clutter Environments
AU - He, Wenjing
AU - Wang, Ju
AU - Shan, Bingqi
AU - Zhang, Qin
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - Autoregressive (AR) modeling of heterogeneous clutter can improve the probability of detecting range-spread targets, but the detector performance diminishes with fewer pulses due to the loss of samples equivalent to the AR order. To mitigate this performance decline, this paper presents an improved model-based Wald detector for range-spread targets in heterogeneous clutter environments, under the assumption of a known clutter covariance matrix based on the Wald test. Furthermore, the covariance matrix is reconstructed using the lower triangular matrix and real symmetric matrix, both of which are composed of the estimated AR parameters. In addition, considering the varying sea clutter under different sea states and across different range cells, an adaptive detector system consisting of detectors in heterogeneous and homogeneous environments is designed. Based on simulated and real clutter data, we demonstrate that the improved detector outperforms the AR model-based detectors with fewer pulses, and that the adaptive detector system can effectively select the optimal detector for the current clutter environment, ensuring high detection performance.
AB - Autoregressive (AR) modeling of heterogeneous clutter can improve the probability of detecting range-spread targets, but the detector performance diminishes with fewer pulses due to the loss of samples equivalent to the AR order. To mitigate this performance decline, this paper presents an improved model-based Wald detector for range-spread targets in heterogeneous clutter environments, under the assumption of a known clutter covariance matrix based on the Wald test. Furthermore, the covariance matrix is reconstructed using the lower triangular matrix and real symmetric matrix, both of which are composed of the estimated AR parameters. In addition, considering the varying sea clutter under different sea states and across different range cells, an adaptive detector system consisting of detectors in heterogeneous and homogeneous environments is designed. Based on simulated and real clutter data, we demonstrate that the improved detector outperforms the AR model-based detectors with fewer pulses, and that the adaptive detector system can effectively select the optimal detector for the current clutter environment, ensuring high detection performance.
KW - adaptive detector system
KW - covariance matrix reconstruction
KW - sea clutter
KW - wald test
UR - http://www.scopus.com/inward/record.url?scp=85214416281&partnerID=8YFLogxK
U2 - 10.1109/EIT63098.2024.10762461
DO - 10.1109/EIT63098.2024.10762461
M3 - Conference contribution
AN - SCOPUS:85214416281
T3 - 2024 3rd International Conference on Electronics and Information Technology, EIT 2024
SP - 125
EP - 130
BT - 2024 3rd International Conference on Electronics and Information Technology, EIT 2024
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 3rd International Conference on Electronics and Information Technology, EIT 2024
Y2 - 20 September 2024 through 22 September 2024
ER -