Through-the-wall radar background clutter suppression method of MIMO antenna

Abstract

The invention provides a background clutter suppression method for an FMCW through-the-wall radar of an MIMO antenna, and the method comprises the steps: carrying out the reordering of original echo data according to an antenna number, carrying out the principal component analysis according to a preset frame length, estimating the background clutter, and updating a background clutter estimation result in real time through continuous iterative operation. The contribution of the current frame to a background estimation result is enhanced, so that background clutters are inhibited to the maximum extent, and the target positioning imaging effect of the radar is improved; in combination with hardware design, the background estimation frame length can be selected to achieve a better background clutter suppression effect.

Description

technical field [0001] The invention belongs to the technical field of radar imaging, and in particular relates to a method for suppressing background clutter of through-wall radar for MIMO antennas. Background technique [0002] Unlike radars used in free space, through-wall radars need to penetrate thick walls to accurately detect and image human targets behind the walls. However, the echo intensity of walls and other obstacles in the room is often higher than that of the human target to be detected, which makes target location extremely difficult, so it is necessary to suppress the background clutter as much as possible before locating the target. [0003] At present, the common clutter suppression methods include frame difference method, cumulative average offset method and exponential weighted offset method. The frame difference method can only observe the target with relatively large motion range. When the target displacement is small, the target will be lost and canno...

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Problems solved by technology

However, the echo intensity of walls and other obstacles in the room is often higher than that of the human target to be detected, which makes the target location very difficult, so it is necessary to suppress the background clutter as much as possible before locating the target

[0003] At present, the common clutter suppression methods include frame difference method, cumulative average offset method and exponential weighted offset method. The frame difference method can only observe the target with relatively large motion range. When the target displacement is small, the target will be lost and cannot be detected; the cumulative average The offset method uses the same weight when accumulating multiple frames, which makes the current frame data contribute less to the overall background estimation; although the exponential weighting method introduces different weights to strengthen the contribution of the current frame to the background estimation, the performance of the algorithm is the same as that of High coupling degree of target movement form

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