Closed-Form Algorithm for 3-D Near-Field OFDM Signal Localization under Uniform Circular Array

Abstract

Due to its widespread application in communications, radar, etc., the orthogonal frequency division multiplexing (OFDM) signal has become increasingly urgent in the field of localization. Under uniform circular array (UCA) and near-field conditions, this paper presents a closed-form algorithm based on phase difference for estimating the three-dimensional (3-D) location (azimuth angle, elevation angle, and range) of the OFDM signal. In the algorithm, considering that it is difficult to distinguish the frequency of the OFDM signal’s subcarriers and the phase-based method is always affected by errors of the frequency estimation, this paper employs sparse representation (SR) to obtain the super-resolution frequencies and the corresponding phases of subcarriers. Further, as the phase differences of the adjacent sensors including azimuth angle, elevation angle and range parameters can be expressed as indefinite equations, the near-field OFDM signal’s 3-D location is obtained by employing the least square method, where the phase differences are based on the average of the estimated subcarriers. Finally, the performance of the proposed algorithm is demonstrated by several simulations.

Mixed Incoherent Far-Field and Near-Field Source Localization under Uniform Circular Array

“…Many super-resolution algorithms have been presented to solve the localization of pure near-field sources (NFSs) condition or pure far-field sources (FFSs) condition [1,2,3,4,5,6]. However, considering some practical applications, such as speaker localization via microphone array and guidance system, speakers may be in the mixed near-field or far-field of the array location.…”

“…However, the aforementioned method has limitation because the configuration of ULA can only be used in the condition of two-dimensional (2-D) localization (elevation angle and range). The array structure of the uniform circular array (UCA) has all-round azimuthal coverage and additional elevation angle information, which is preferable over the array structure of ULA [2,3,4,5]. As for the localization of 3-D condition (azimuth angle, elevation angle and range), based on the centro-symmetric configuration of UCA, Wu et al [4] employed 2-D multiple signal classification (MUSIC) method to search the 2-D direction of arrivals (DOAs), and further utilized 1-D MUSIC method to estimate corresponding ranges, which can handle multiple near-field sources.…”