Wall Clutter Mitigation Algorithm Based On Kalman Filter In Spread Spectrum Through-the-wall Radar

The Spread Spectrum Through-the-Wall Radar(SS-TWR)can carry out real-time detection of the targets behind the wall.It is widely used in the defense and military departments,rescue and relief work,civilian facilities,due to it has the advantage of good anti-interference,tow probability of interception and accurate estimation of arrival time.However,owing to the existence of the extra wall,the originally weak target signal is submerged in the direct wave and wall refection,accompanied by the generation of time delay and signal energy attenuationThis paper proposes a clutter suppression algorithm based on Kalman filter for static target detection in SS-TWR.It is mainly composed of three modules,namely,the tracking of sub-clutter,the Kalman accurate filtering and the power inversion.The strong clutter signal is reconstructed and removed by means of multi-layer loop.The algorithm can obtain accurate echo delay estimation,target information and clear target image under strong noise environment.In order to further improve the filtering accuracy,on the basis of this algorithm,a clutter supression algorithm based on Exte nded Kalman Filter(EKF)or Improved Unscented Kalman Filter(IUKF)is proposed consecutively.Compared with the previous,the latter algorithm further improves the filtering accuracy performance and achieves at least the Taylor accuracy of at least three orders while maintaining the same amount of computation.Compared with the traditional UKF,the proposed algorithm based on IUKF reduces the total amount of calculation to roughly half of the original.In addition,the performances of the improved algorithms are compared with other clutter suppression algorithms.The experimental results show that the target positioning accuracy error is 2cm,the image improvement factor is improved by 1-5dB,and the clear target imaging results can be obtained under the strong noise environment with a signal-to-noise ratio of-22dB.