Due to the overlapping functionality between communication devices and radar systems, communication devices can also be utilized for target detection. However, traditional communication protocol adopts explicit feedback to transmit information, leading to the failure of communication equipment detection to retain perceptual information. Therefore, the decomposition process of explicit feedback can be improved, so as to realize the awareness of environmental objectives in the communication gap. In MIMO systems, beamforming is a technology used at the transmitter to generate a steering matrix based on MIMO channel information, thereby enhancing the channel performance at the receiver. At present, display feedback beamforming is the mainstream approach of beamforming in communication. However, the feedback matrix obtained by the traditional decomposition method usually loses some important information, which limits the functionality of using Wi-Fi signals for target detection. It is found that the eigenvector obtained by the traditional singular value decomposition method can not retain the distance and velocity information of the target. In this paper, a novel decomposition method is proposed based on the covariance matrix of the channel matrix. Firstly, the left singular value matrix is obtained, and then an improved right singular value matrix is further obtained by using the corresponding relationship between the orthogonal vectors of the two unitary matrixes. The improved result retains the distance, speed and angle information of the target, and greatly improves the effectiveness of the feedback information. Finally, the effectiveness of the proposed method is verified through simulation.