DOA Estimation of Underwater Acoustic Signals Based on PCA-kNN Algorithm
Yuji Liu, Huixiu Chen, Biao Wang · 2020 International Conference on Computer Information and Big Data Applications (CIBDA) · 2020
Array signal processing is an important branch of signal processing, and direction of arrival (DOA) estimation is an important research direction in array signal processing, involving smart antenna, underwater acoustic array and other fields. This paper presents a narrow-band DOA estimation algorithm based on PCA (Principal Component Analysis) and kNN (k-Nearest Neighbor). Firstly, PCA algorithm is used to reduce the dimension of the covariance matrix of the signal to reduce the complexity of the model. Then kNN algorithm is used to build the classification model. Through the prior knowledge of the classification about covariance matrix and the corresponding direction, the unknown signal can be estimated quickly and accurately. In this paper, the software simulation is used to prove the validity and reliability of the algorithm by comparing with kNN algorithm and SVM algorithm.