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This paper addresses the adaptive radar target detection problem in the presence of Gaussian interference with unknown statistical properties. To this end, the problem is first formulated as a binary hypothesis test, and then we derive a…

Signal Processing · Electrical Eng. & Systems 2025-03-05 Chaoran Yin , Tianqi Wang , Linjie Yan , Chengpeng Hao , Alfonso Farina , Danilo Orlando

The development of sliding window detection processes, based upon a single cell under test, and operating in clutter modelled by a Pareto distribution, has been examined extensively. This includes the construction of decision rules with the…

Applications · Statistics 2019-01-03 Graham V. Weinberg

This paper deals with the problem of adaptive multidimensional/multichannel signal detection in homogeneous Gaussian disturbance with unknown covariance matrix and structured (unknown) deterministic interference. The aforementioned problem…

Information Theory · Computer Science 2016-06-23 Domenico Ciuonzo , Antonio De Maio , Danilo Orlando

We apply adaptive sensing techniques to the problem of locating sparse metallic scatterers using high-resolution, frequency modulated continuous wave W-band RADAR. Using a single detector, a frequency stepped source, and a lateral…

This paper focuses on the design of a robust decision scheme capable of operating in target-rich scenarios with unknown signal signatures (including their range positions, angles of arrival, and number) in a background of Gaussian…

Signal Processing · Electrical Eng. & Systems 2025-04-02 Linjie Yan , Chengpeng Hao , Sudan Han , Giuseppe Ricci , Zhanhao Hu , Danilo Orlando

Detecting small targets in sea clutter is challenging due to dynamic maritime conditions. Existing solutions either model sea clutter for detection or extract target features based on clutter-target echo differences, including statistical…

Computer Vision and Pattern Recognition · Computer Science 2025-01-10 Junjie Wang , Yuze Gao , Dongying Li , Wenxian Yu

This paper proposes a novel approach to robust radar detection of range-spread targets embedded in Gaussian noise with unknown covariance matrix. The idea is to model the useful target echo in each range cell as the sum of a coherent signal…

Signal Processing · Electrical Eng. & Systems 2022-10-04 Angelo Coluccia , Alessio Fascista , Giuseppe Ricci

This paper addresses two critical limitations in diagonally loaded (DL) adaptive matched filter (AMF) detector: (1) the lack of CFAR property with respect to arbitrary covariance matrices, and (2) the absence of selection criteria for…

Signal Processing · Electrical Eng. & Systems 2025-12-18 Jie Zhou , Junhao Xie

A cognitive fully adaptive radar (CoFAR) adapts its behavior on its own within a short period of time in response to changes in the target environment. For the CoFAR to function properly, it is critical to understand its operating…

Signal Processing · Electrical Eng. & Systems 2024-08-13 Kunwar Pritiraj Rajput , Bhavani Shankar M. R. , Kumar Vijay Mishra , Muralidhar Rangaswamy , Bjorn Ottersten

Passive and bistatic radar systems are often limited by strong clutter and direct-path interference that mask weak moving targets. Conventional cancellation methods such as the extensive cancellation algorithm require careful tuning and can…

Optimization and Control · Mathematics 2026-01-01 Yifan He , Griffin Kearney , Makan Fardad

Multi-array systems are widely used in sonar and radar applications. They can improve communication speeds, target discrimination, and imaging. In the case of a multibeam sonar system that can operate two receiving arrays, we derive new…

Applications · Statistics 2024-02-28 Olivier Lerda , Ammar Mian , Guillaume Ginolhac , Jean-Philippe Ovarlez , Didier Charlot

An introduction to the theory of sliding window detection processes, used as alternatives to optimal Neyman-Pearson based radar detectors, is presented. Included is an outline of their historical development, together with an explanation…

Applications · Statistics 2017-09-29 Graham V. Weinberg

We describe an efficient and fault-tolerant algorithm for distributed cyclic garbage collection. The algorithm imposes few requirements on the local machines and allows for flexibility in the choice of local collector and distributed…

Distributed, Parallel, and Cluster Computing · Computer Science 2007-05-23 N. Allen , T. Terriberry

In this paper, we develop a new elegant framework relying on the Kullback-Leibler Information Criterion to address the design of one-stage adaptive detection architectures for multiple hypothesis testing problems. Specifically, at the…

Signal Processing · Electrical Eng. & Systems 2021-03-23 Pia Addabbo , Sudan Han , Fillippo Biondi , Gaetano Giunta , Danilo Orlando

This paper considers the design of tunable decision schemes capable of rejecting with high probability mismatched signals embedded in Gaussian interference with unknown covariance matrix. To this end, a sparse recovery technique is…

Signal Processing · Electrical Eng. & Systems 2020-04-29 Sudan Han , Luca Pallotta , Xiaotao Huang , Gaetano Giunta , Danilo Orlando

A class of novel STAP algorithms based on sparse recovery technique were presented. Intrinsic sparsity of distribution of clutter and target energy on spatial-frequency plane was exploited from the viewpoint of compressed sensing. The…

Information Theory · Computer Science 2009-04-09 Hao Zhang , Gang Li , Huadong Meng

The accelerated failure time (AFT) model is widely used to analyze relationships between variables in the presence of censored observations. However, this model relies on some assumptions such as the error distribution, which can lead to…

Methodology · Statistics 2026-02-10 Sangkon Oh , Hyunjae Lee , Sangwook Kang , Byungtae Seo

Off-grid targets whose Doppler (or angle) does not lie on the discrete processing grid can severely degrade classical normalized matched-filter (NMF) detectors: even at high SNR, the detection probability may saturate at operationally…

Signal Processing · Electrical Eng. & Systems 2026-02-17 Yadang Alexis Rouzoumka , Jean Pinsolle , Eugénie Terreaux , Christèle Morisseau , Jean-Philippe Ovarlez , Chengfang Ren

Compared with the sparse recovery process in traditional compressed sensing (CS) radar detector CAMP, vector AMP deep unfolding (VAMP-DU) can achieve sparse recovery over a broader range of observation matrices, with faster convergence…

Signal Processing · Electrical Eng. & Systems 2026-01-08 Haoyun Zhang , Jianghong Han , Xueqian Wang , Gang Li , Xiao-Ping Zhang

Practical ISAC is constrained by static clutter and NLoS multipath, which obscure target-coupled echoes and induce spurious peaks for beam alignment. Existing receiver-side methods largely model targets as passive scatterers, limiting the…

Information Theory · Computer Science 2026-05-27 Xuehui Dong , Kai Wan , Gui Zhou , Chen Shao , Miyu Feng , Robert Caiming Qiu