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After obtaining an accurate approximation for $ARL_0$, we first consider the optimal design of weight parameter for a multivariate EWMA chart that minimizes the stationary average delay detection time (SADDT). Comparisons with moving…

Statistics Theory · Mathematics 2022-06-24 Yanhong Wu , Wei Biao Wu

Radar ensures robust sensing capabilities in adverse weather conditions, yet challenges remain due to its high inherent noise level. Existing radar odometry has overcome these challenges with strategies such as filtering spurious points,…

Robotics · Computer Science 2025-02-25 Wooseong Yang , Hyesu Jang , Ayoung Kim

The compressed sensing (CS) model can represent the signal recovery process of a large number of radar systems. The detection problem of such radar systems has been studied in many pieces of literature through the technology of debiased…

Signal Processing · Electrical Eng. & Systems 2023-07-03 Siqi Na , Yoshiyuki Kabashima , Takashi Takahashi , Tianyao Huang , Yimin Liu , Xiqin Wang

In this paper, we propose a novel framework for the joint identification of system dynamics and noise covariance in linear systems, under general noise distributions beyond Gaussian. Specifically, we would like to simultaneously estimate…

Systems and Control · Electrical Eng. & Systems 2026-04-16 Yang Hu , Na Li

Modern autonomous navigation for unmanned ground vehicles relies on different estimators to fuse inertial sensors and GNSS measurements. However, the constant noise covariance matrices often struggle to account for dynamic real-world…

Robotics · Computer Science 2026-03-26 Gal Versano , Itzik Klein

Accurately estimating the statistical properties of noise is important in data analysis for space-based gravitational wave detectors. Noise in different time-delay interferometry channels correlates with each other. Many studies often…

Instrumentation and Methods for Astrophysics · Physics 2025-06-18 Ya-Nan Li , Yi-Ming Hu , En-Kun Li

We propose a nonparametric density estimator based on the Gaussian process (GP) and derive three novel closed form learning algorithms based on Fisher divergence (FD) score matching. The density estimator is formed by multiplying a base…

Machine Learning · Computer Science 2025-11-17 John Paisley , Wei Zhang , Brian Barr

We consider the use of machine learning for hypothesis testing with an emphasis on target detection. Classical model-based solutions rely on comparing likelihoods. These are sensitive to imperfect models and are often computationally…

Machine Learning · Computer Science 2022-06-14 Tzvi Diskin , Uri Okun , Ami Wiesel

Structured covariance matrix estimation in the presence of missing data is addressed in this paper with emphasis on radar signal processing applications. After a motivation of the study, the array model is specified and the problem of…

Signal Processing · Electrical Eng. & Systems 2022-12-09 Augusto Aubry , Antonio De Maio , Stefano Marano , Massimo Rosamilia

In this paper, a class of nonlinear MMSE multiuser detectors are derived based on a multivariate Gaussian approximation of the multiple access interference. This approach leads to expressions identical to those describing the probabilistic…

Information Theory · Computer Science 2007-07-13 Peng Hui Tan , Lars K. Rasmussen

Non-data-aided (NDA) parameter estimation is considered for binary-phase-shift-keying transmission in an additive white Gaussian noise channel. Cramer-Rao lower bounds (CRLBs) for signal amplitude, noise variance, channel reliability…

Information Theory · Computer Science 2007-07-13 Fredrik Brannstrom , Lars K. Rasmussen

The problem of noise covariance matrix identification of stochastic linear time-varying state-space models is addressed. The measurement difference method (MDM) is generalized to time-varying dimensions of the measurement and control. Three…

Signal Processing · Electrical Eng. & Systems 2024-12-11 Oliver Kost , Jindrch Dunik , Ondrej Straka

Second-order information -- such as curvature or data covariance -- is critical for optimisation, diagnostics, and robustness. However, in many modern settings, only the gradients are observable. We show that the gradients alone can reveal…

Machine Learning · Computer Science 2026-04-08 Arash Jamshidi , Katsiaryna Haitsiukevich , Kai Puolamäki

A joint robust transmit/receive adaptive beamforming for multiple-input multipleoutput (MIMO) radar based on probability-constrained optimization approach is developed in the case of Gaussian and arbitrary distributed mismatch present in…

Information Theory · Computer Science 2016-03-03 Weiyu Zhang , Sergiy A. Vorobyov

Estimating conditional dependence graphs and precision matrices are some of the most common problems in modern statistics and machine learning. When data are fully observed, penalized maximum likelihood-type estimators have become standard…

Machine Learning · Statistics 2019-04-09 Roger Fan , Byoungwook Jang , Yuekai Sun , Shuheng Zhou

The fusion between an inertial navigation system and global navigation satellite systems is regularly used in many platforms such as drones, land vehicles, and marine vessels. The fusion is commonly carried out in a model-based extended…

Systems and Control · Electrical Eng. & Systems 2022-09-05 Barak Or , Itzik Klein

In this paper, we design constant modulus probing waveforms with good correlation properties for collocated multi-input multi-output (MIMO) radar systems. The main content is as follows: first, we formulate the design problem as a fourth…

Signal Processing · Electrical Eng. & Systems 2019-09-04 Jiangtao Wang , Yongchao Wang

In this paper, we consider a multiple-input multiple-output (MIMO) radar system for localizing a target based on its reflected echo signals. Specifically, we aim to estimate the random and unknown angle information of the target, by…

Information Theory · Computer Science 2023-05-16 Chan Xu , Shuowen Zhang

A MIMO radar system is proposed for obtaining angle and Doppler information on potential targets. Transmitters and receivers are nodes of a small scale wireless network and are assumed to be randomly scattered on a disk. The transmit nodes…

Information Theory · Computer Science 2015-05-14 Yao Yu , Athina P. Petropulu , H. Vincent Poor

Maneuvering target tracking is a challenging problem for sensor systems because of the unpredictability of the targets' motions. This paper proposes a novel data-driven method for learning the dynamical motion model of a target.…

Signal Processing · Electrical Eng. & Systems 2022-11-28 Mengwei Sun , Mike E. Davies , Ian K. Proudler , James R. Hopgood