Abstract
The task of synthesizing optimal signal processing in synthetic aperture radars equipped with a selection mode of power lines was solved by the maximum likelihood method. The distinguishing features of power lines from the earth's surface selected polarization and Doppler differences. The useful signal at the output of the coherent receiver specified in an analytical form with a complex envelope and high-frequency harmonic oscillations. The background radiation of the underlying surface is presented in a stochastic form and is completely determined by the matrix of correlation functions. The internal noise of a multichannel receiver is described by a delta-correlated random Gaussian process with the same power spectral density in different observation channels. Since the background radiation of the earth's surface is correlated in time and at different polarizations functional likelihood recorded with the inverse matrix inverse correlation functions. The obtained optimal algorithm consists of suppression of passive interference in decor-leveling filters, optimal coherent accumulation of trajectory signals for synthesizing the on-board antenna aperture, and their optimal filtering in filters matched with the reference signal. Simultaneous use of Doppler and polarization differences between wanted signals and passive interference allows you to effectively allocate power lines against the background of reflections from the ground in multichannel synthetic aperture radars. The proposed sequence of operations on the received oscillations can be a functional addition to the operating modes of aerospace-based cognitive radars, adapting by the covariance scattering matrix of the underlying surface known in advance or measured during remote sensing. The block diagram of a multichannel onboard polarization radar with a synthesized antenna aperture is synthesized based on the obtained results. The development of such a radar is relevant for a collision warning system for helicopter pilots, especially in bad weather conditions at any time of the year, day and night.
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