Study on a High-Resolution Map Generation Method by Mitigating Multipath Effects in Indoor Environments

This study proposes a novel method for accurately identifying target information by mitigating multipath effects in indoor environments. First, range–velocity maps were generated by applying a 2D fast Fourier transform to received data. Then, the influence of stationary clutter was decreased using the exponential moving average. Next, multiple range–velocity maps were grouped, and thresholds were set based on the variance along the range axis of the range–velocity maps and correlation coefficients to select the range–velocity maps for signal processing. Then, eigenvalue decomposition was applied to the selected range–velocity maps to create projection matrices, and dynamic multipath effects were mitigated by projecting the previously selected range–velocity maps. Subsequently, velocity–angle maps were produced using the Capon method based on range–velocity maps with reduced dynamic multipath effects. Finally, noncoherent integration was applied within the group. The performance of the proposed method was verified through experimental measurements. The proposed method improved the signal-to-noise ratio by up to 18.7 dB, enhanced detection performance, reduced the sidelobe level by up to 2.4 dB, and decreased the total frame processing time by up to 12.47 %.