Maximum Likelihood Algorithm for Time-Delay Based Multistatic Target Localization
Kuntal Panwar, Prabhu Babu, Petre Stoica
Abstract
In this letter we address the problem of multistatic target localization using time-delay measurements corrupted by noise with unknown non-uniform variances. More concretely, we consider the problem of joint maximum likelihood (ML) estimation of the target position and the noise variances, for which we propose a majorization-minimization based algorithm. The proposed approach is compared with state-of-the-art algorithms, and the simulation results show the excellent accuracy of our algorithm.
Topics & Concepts
AlgorithmPosition (finance)Computer scienceNoise (video)Noise measurementMaximum likelihoodMinificationMultistatic radarArtificial intelligenceMathematicsNoise reductionStatisticsRadarTelecommunicationsBistatic radarImage (mathematics)FinanceRadar imagingProgramming languageEconomicsIndoor and Outdoor Localization TechnologiesTarget Tracking and Data Fusion in Sensor NetworksSparse and Compressive Sensing Techniques