Generalized Likelihood Ratio Test (GLRT)

This paper presents a unified framework, based on the generalized likelihood (GL), for the detection of targets and the estimation of their direction of arrival (DoA), when operating with modern radar systems that have general antenna array configurations, which contain a mixture of high- and low-gain beams. Adaptive processing structures are presented to remove both side lobe and main lobe

We tackle distributed detection of a non-cooperative target with a Wireless Sensor Network (WSN). When the target is present, sensors observe an (unknown) deterministic signal with attenuation depending on the distance between the sensor and the (unknown) target positions, embedded in symmetric and unimodal noise. The Fusion Center (FC) receives quan-tized sensor observations through error-prone Binary Symmetric Channels (BSCs) and is in charge of performing a more-accurate global decision. The resulting problem is a two-sided parameter testing with nuisance parameters (i.e. the target position) present only under the alternative hypothesis. After introducing the Generalized Likelihood Ratio Test (GLRT) for the problem, we develop a novel fusion rule corresponding to a Generalized Rao (G-Rao) test, based on Davies' framework, to reduce the computational complexity. Also, a rationale for threshold-optimization is proposed and confirmed by simulations. Finally, the aforementioned rules are compared in terms of performance and computational complexity.

This paper investigates the application of the Generalized Likelihood Ratio Test detector to the Global Navigation Satellite System array-based acquisition problem. We consider an unstructured channel model which includes colored noise with an arbitrary covariance matrix. We show that the proposed test function is a Constant False Alarm Rate detector and we provide closed form expressions for false alarm, detection probabilities, and the Receiver Operating Characteristic. Furthermore, this work analyzes the Sample Covariance Matrix structure and the capability of the detector to reject uncorrelated interferences. Simulation results validate the theoretical analysis.

Abstract The performance of subsurface deep sounding is investigated with reference to the radar sounder, MARSIS (Mars advanced radar for subsurface and ionosphere sounding), aboard the Mars Express mission, designed to investigate the presence of water-related ...

This paper describes a data reconciliation and gross error detection software (RAGE) to convert raw data into useful plant information for performance analysis, process control and circuit optimization. The conventional data reconcillation tools used in mineral processing industries generally focus on solid and component balances. RAGE uses Successive Quadratic Programming for data reconciliation and Generalized Likelihood Ratio Test with serial compensation technique for gross error detection. The software not only focuses on solid and component balances but also gives liquid balance across the entire circuit.

This paper proposes orthogonal Discrete Frequency Coding Space Time Waveforms (DFCSTW) for Multiple Input and Multiple Output (MIMO) radar detection in compound Gaussian clutter. The proposed orthogonal waveforms are designed considering the position and angle of the transmitting antenna when viewed from origin. These orthogonally optimized show good resolution in spikier clutter with Generalized Likelihood Ratio Test (GLRT) detector. The simulation results show that this waveform provides better detection performance in spikier Clutter.

In this paper we propose the use of -divergences as test statistics to ver- ify simple hypotheses about a one-dimensional parametric diusion process dXt = b(Xt; )dt+ (Xt; )dWt, from discrete observationsfXti;i = 0;:::;ng with ti = i n, i = 0; 1;:::;n, under the asymptotic scheme n ! 0, n n ! 1 and n 2n ! 0. The

This paper investigates the application of the Generalized Likelihood Ratio Test detector to the Global Navigation Satellite System array-based acquisition problem. We consider an unstructured channel model which includes colored noise with an arbitrary covariance matrix. We show that the proposed test function is a Constant False Alarm Rate detector and we provide closed form expressions for false alarm, detection probabilities, and the Receiver Operating Characteristic. Furthermore, this work analyzes the Sample Covariance Matrix structure and the capability of the detector to reject uncorrelated interferences. Simulation results validate the theoretical analysis.

High ground-level ozone (GLO) concentrations will adversely affect human health, vegetations as well as the ecosystem. Therefore, continuous monitoring for GLO trends is a good practice to address issues related to air quality based on high concentrations of GLO. The purpose of this study is to introduce stationary and non-stationary model of extreme GLO. The method is applied to 25 selected stations in Peninsular Malaysia. The maximum daily GLO concentration data over 8 hours from year 2000 to 2016 are used. The factors of this distribution are anticipated using maximum likelihood estimation. A comparison between stationary (constant model) and non-stationary (linear and cyclic model) is performed using the likelihood ratio test (LRT). The LRT is based on the larger value of deviance statistics compared to a chi-square distribution providing the significance evidence to non-stationary model either there is linear trend or cyclic trend. The best fit model between selected models is ...

Early radar systems are designed based on a single antenna. Radar designers are currently inter-ested to develop multi-antenna radar systems. MIMO radars utilize a multi-static architecture in which spatial coherency assumption for both transmitter antenna elements and ...

In many applications, quality of a process is best characterized by a functional relationship between a response variable and one or more explanatory variables. Profile monitoring is used for checking the stability of this relationship over time. Control charts based on nonparametric regression are particularly useful when the in-control (IC) or out-of-control (OC) relationship is too complicated to be specified parametrically. This paper proposes a novel nonparametric control chart, using a sequential change-point formulation with generalized likelihood ratio tests. Its control limits are determined by a bootstrap procedure. This chart can be implemented without any knowledge about the error distributions, as long as a few IC profiles are available beforehand. Moreover, benefiting from certain good properties of the dynamic change-point approach and of the proposed charting statistic, the proposed control chart not only offers a balanced protection against shifts of different magni...