Adaptive Algorithm of Maneuvering Target Tracking in Complex Jamming Situation for Multifunctional Radar with Phased Antenna Array


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Resumo

Adaptive multimodel algorithms based on the target movement model in the form of discrete stochastic dynamic system with random structure are adequate to the problem of target tracking based on data of the multifunctional radar station (MFRS) with phased antenna array (PAA) under conditions of complex dynamically varying signal and jamming situation. This study presents an optimal and quasioptimal algorithms of adaptive estimation of movement parameters of maneuvering targets in the Cartesian coordinate system for MFRS with PAA based on the mathematical tools of mixed Markov processes in discrete time. They describe the evolution of joint a posteriori probability density of the vector of target movement parameters and switching variable determining the mode of its movement, while the filters implementing them are referred to the class of devices with feedbacks between channels. The identification of blips in the tracking strobe is performed in the spherical coordinate system by selecting the blip, which is the closest to the strobe center. The efficiency analysis of the developed tracking algorithm is performed by using the test paths of two targets with different intensities of the maneuver and parameters of tracking modes. The accuracy characteristics of adaptive filter and indicators of the tracking efficiency at different false alarm probabilities have been determined.

Sobre autores

T. Baringolts

Kvant Radar Systems Scientific Research Institute

Autor responsável pela correspondência
Email: kvant-rs@ln.ua
Ucrânia, Kyiv

D. Domin

Kvant Radar Systems Scientific Research Institute

Email: s.zhuk@kpi.ua
Ucrânia, Kyiv

S. Zhuk

National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”

Autor responsável pela correspondência
Email: s.zhuk@kpi.ua
Ucrânia, Kyiv

V. Tsisarzh

Kvant Radar Systems Scientific Research Institute

Email: s.zhuk@kpi.ua
Ucrânia, Kyiv


Declaração de direitos autorais © Allerton Press, Inc., 2019

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