卷 62, 编号 7 (2019)

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.

Thepaper proposes a nonlocal method of additive noise suppression in digital image based on presenting the image in matrix phase space and using nonconventional methods of multivariate statistical analysis, namely, the surrogate data technology that makes it possible to generate a pseudo-ensemble of surrogate images with their subsequent averaging using a single snapshot. This approach is based on properties of the coherent accumulation of signal component of the observation and noncoherent accumulation of its noise component as the size of observation ensemble increases that allows us to partially solve the contradiction between the denoising level and the distortion or loss of small-sized details of image, i.e. reduction of spatial resolution. The simulation modeling of the proposed method of generalized SDT-filtering of noise was conducted using the application software package of MathCad and Matlab. A comparative analysis of the spatial resolution of the proposed and several known methods of denoising has been carried out using the resolution-measurement criterion and the modified Rayleigh criterion. As is shown, the proposed method demonstrates a better spatial resolution as compared to the most common methods of denoising that is confirmed by the results of simulation modeling.