Kyun-Kyung Lee

Closed-Form Algorithm for 3-D Single-Source Localization With Uniform Circular Array

This letter presents a closed-form algorithm for estimating the three-dimensional (3-D) location (azimuth angle, elevation angle, and range) of a single source with uniform circular array (UCA). Based on a correlation, a closed-form method was recently proposed to estimate the two-dimensional (2-D) angle (azimuth and elevation angle) of a single source with UCA. This letter proposes a generalized algorithm that extends the previous work to a 3-D problem. The proposed algorithm provides all the estimation parameters simultaneously and is computationally simple. Numerical examples are also presented to demonstrate the performance of the proposed algorithm.

2-D Nominal Angle Estimation of Multiple Coherently Distributed Sources in a Uniform Circular Array

A novel algorithm is presented to estimate 2-D nominal angles of multiple coherently distributed sources in a uniform circular array (UCA). Based on a decoupled generalised array response vector and single centro-symmetric UCA, the proposed algorithm can estimate the nominal angles without any information about the deterministic angular distribution functions of the sources or additional array structures.

Position Estimation of Underwater Target Using Proximity Sensor with Bearing Information

Proximity sensor networks are aimed at estimation kinematic state of target using estimated position of the target by each sensor node or target parameter. To analyze the kinematic state of target, traditional approaches require detections on multiple sensors, very large number of sensors to achieve acceptable performance. In this paper, we propose a novel method which can estimate predicted position of the underwater target using minimum proximity sensor with bearing information to this problem. The proposed algorithm was verified performance through simulation.

Near-field Source Localization Method using Matrix Pencil

In this paper, near-field source localization algorithm is presented using Matrix Pencil in Uniform Linear Array(ULA). Based on the centrosymmetry of the ULA, the proposed algorithm decouples the steering vectors which allow for the bearing estimation using Matrix pencil. With estimated bearing, the range estimation of each source is consequently obtained by defining 1D MUSIC spectrum. Simulation results are presented to validate the performance of the proposed algorithm.

Decoupled Location Parameter Estimation of 3-D Near-Field Sources in a Uniform Circular Array using the Rank Reduction Algorithm

An algorithm is presented for estimating the 3-D location (i.e., azimuth angle, elevation angle, and range) of multiple sources with a uniform circular array (UCA) consisting of an even number of sensors. Recently the rank reduction (RARE) algorithm for partly-calibrated sensor arrays was developed. This algorithm is applicable to sensor arrays consisting of several identically oriented and calibrated linear subarrays. Assuming that a UCA consists of M sensors, it can be divided into M/2 identical linear subarrays composed of two facing sensors. Based on the structure of the subarrays, the steering vectors are decomposed into two parts: range-independent 2-D direction-of-arrival (DOA) parameters, and range-relevant 3-D location parameters. Using this property we can estimate range-independent 2-D DOAs by using the RARE algorithm. Once the 2-D DOAs are available, range estimation can be obtained for each source by defining the 1-D MUSIC spectrum. Despite its low computational complexity, the proposed algorithm can provide an estimation performance almost comparable to that of the 3-D MUSIC benchmark estimator.