Wide-area random thin cloth array multi-target positioning method based on energy separation

Abstract

The invention discloses a wide-area random sparse cloth array multi-target positioning method based on energy separation, relates to the field of multi-target positioning, and mainly solves the problem of multi-target resolution in a wide-area random sparse cloth array detection scene. The method comprises the following steps of: 1, determining basic parameters of the wide-area random sparse array system, wherein the basic parameters comprise receiving node position coordinates, carrier frequency, scanning range and interval, and searching range and interval; 2, performing matching search on the measured energy field and the matched energy field based on a field matching method to determine a relatively strong target position; 3, after a strong target position is known, subtracting the theoretical echo energy matrix corresponding to the target from the energy information measurement matrix to realize energy elimination; and 4, carrying out matching search on the energy information measurement matrix after the strong target energy information is removed and the energy information matching matrix again to obtain a relatively weak target position. According to the method, multi-target position estimation is realized by utilizing amplitude-phase characteristic separation of a multi-target echo energy field, and the capability of distinguishing strong and weak multiple targets with relatively large energy difference is improved.

Description

technical field [0001] The invention relates to the field of multi-target positioning of a wide-area random sparse array, and is particularly suitable for multi-target positioning of a near-field detection scene of a wide-area random sparse array. Background technique [0002] The wide-area random sparse array system mainly adopts the information-level fusion target location method based on single-station measurement information estimation, and it is difficult to exert the optimal performance of the system. There are two main methods of signal level fusion positioning in the current wide-area random sparse array system. The most direct method is spatial grid division, and the blind search method is to use the main lobe to scan the beam in the three dimensions of azimuth-elevation-distance. The wide-area random sparse array system has a large aperture and a low main-side lobe ratio, so this method has the problem of poor multi-target resolution; another feasible method is to ...

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Problems solved by technology

[0002] The wide-area random sparse array system mainly adopts the information-level fusion target positioning method based on single-station measurement information estimation, which is difficult to exert the optimal performance of the system

There are currently two main signal-level fusion positioning methods for wide-area random sparse array systems. The most direct method is airspace grid division, and the blind search method uses the main lobe to scan the beam in the three dimensions of azimuth-pitch-distance. The wide-area random sparse array system has large aperture and low main-side lobe ratio, so this method has the problem of poor multi-target resolution; another feasible method is to construct a cost function, directly process the received signal, and use the MUSIC algorithm and ESPIRT algorithm to achieve Multi-target positioning, there are problems of poor robustness and large amount of calculation in multi-target positioning

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