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Neyman's C(α) test and Rao's efficient score test for composite hypotheses
Statistics & Probability Letters, 1991zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Kocherlakota, S., Kocherlakota, K.
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Parametric Rao Test for Multichannel Adaptive Signal Detection
IEEE Transactions on Aerospace and Electronic Systems, 2007The parametric Rao test for a multichannel adaptive signal detection problem is derived by modeling the disturbance signal as a multichannel autoregressive (AR) process. Interestingly, the parametric Rao test takes a form identical to that of the recently introduced parametric adaptive matched filter (PAMF) detector for space-time adaptive processing ...
null Kwang June Sohn +2 more
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The arm detection based on Rao test method
2007 International Symposium on Intelligent Signal Processing and Communication Systems, 2007Firstly, aim at the different radar echo characteristic of anti-radar missile (ARM) and its aircraft, a correlative canceller is proposed to restrain the aircraft signal through estimating its Doppler frequency. Then based on the assumption of autoregressive (AR) process noise, a detection algorithm is derived to implement the ARM target detection ...
null Fang Qianxue +2 more
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Estimation and Tests for Departures from Rao‐Structured Covariance Matrices
Biometrical Journal, 1987AbstractFor linear models, a measure of departure of a variance‐covariance matrix from Rao‐structure (Rao, 1967) is proposed. Relevant estimation and testing problems are discussed. Illustrative examples are also presented.
Ghosh, Subir, Gokhale, D. V.
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A Rao Test With Enhanced Selectivity Properties in Homogeneous Scenarios
IEEE Transactions on Signal Processing, 2010This correspondence focuses on the design of a selective receiver for homogeneous scenarios. To this end, at the design stage it is assumed that the cell under test contains a noise-like interferer in addition to thermal noise, clutter, and to the possible signal of interest; a set of secondary data, free of signal components, is available: such data ...
D. Orlando, RICCI, Giuseppe
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Adjustments of Rao’s Score Test for Distributional and Local Parametric Misspecifications
Journal of Econometric Methods, 2017Abstract Rao’s (1948) seminal paper introduced a fundamental principle of testing based on the score function and the score test has local optimal properties. When the assumed model is misspecified, it is well known that Rao’s score (RS) test loses its optimality. A model could be misspecified in a variety of ways.
Bera, Anil K. +4 more
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Persymmetric Rao test for MIMO radar in Gaussian disturbance
Signal Processing, 2019Abstract This paper considers the target detection problem in multiple-input multiple-output radar where the disturbance covariance matrix is unknown. Based on the Rao criterion, a persymmetric Rao test is designed by exploiting the persymmetric structure of the disturbance covariance matrix.
Jun Liu +4 more
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Bayesian Rao and Wald test for radar adaptive detection
2010 IEEE International Conference on Acoustics, Speech and Signal Processing, 2010This paper deals with the adaptive detection of a signal of interest in the presence of Gaussian noise with unknown covariance matrix (CM). To this end, we resort to a Bayesian approach based on a suitable model for the probability density function (PDF) of unknown CM.
Yu Zhou, Lin-rang Zhang
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On two-dimensional statistical resolution limit with Rao test
2017 IEEE 9th International Conference on Communication Software and Networks (ICCSN), 2017Statistical Resolution Limit (SRL) is defined as the minimal separation to resolve two closely-spaced signals. It is a significant metric to quantify performance in parameter estimation problems. For SRL analysis, since the method based on the Generalized Likelihood Ratio test (GLRT) has the problem of high computational complexity, we put forward a ...
Minhong Sun, Yanfang Liu
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Rao test for distributed target detection with partial observation
2017 IEEE Radar Conference (RadarConf), 2017This paper considers the detection of a distributed target in the partial observation scenario, where only a set of receiving data with missing entries is available. The target is assumed to be obscured by complex Gaussian disturbance (clutter plus noise) with structured covariance matrix.
Le Xiao +3 more
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