Evaluating Two Array Autocalibration Methods with Multifrequency HF Radar Current Measurements

Abstract

One pivotal factor affecting the accuracy of HF radar current measurements is the direction of arrival (DOA) estimation performance of the current signal. The beamforming technology or superresolution algorithm cannot always perform best in practical applications because of the phase errors existing in array channels. These phase errors, which cause uncertain estimation of DOA, lead to confused values in radial current maps. To solve this problem, this paper is focused on discussing the performances of two autocalibration methods using sea echoes for multifrequency high-frequency (MHF) radar current measurements. These two array calibration methods, based on maximum likelihood (ML) and multiple signal classification (MU), first seek single-DOA sea echoes and then gather them for array calibration using different cost functions. The ML and MU methods provide approximate mean phases, while the standard phase errors of the MU method are smaller. After array calibration using these two methods, the results show significant improvements in current retrievals. Comparisons between the MHF radar and ADCPs reveal that array calibration using the ML and MU methods also improves the estimation of radial currents clearly, with correlation coefficients over 0.93 and rms differences of 0.09-0.18 m s 21 at different operating frequencies and sampling locations. The performance of the bearing offset is also improved. Only small bearing offsets less than 108 exist in radial current measurements. Therefore, this paper demonstrates that array calibration is a crucial part for current measurements, especially for direction-finding HF radar.

Validation and Evaluation of a Ship Echo-Based Array Phase Manifold Calibration Method for HF Surface Wave Radar DOA Estimation and Current Measurement

“…The MU method forms a cost function using the eigenstructure decomposition of single-DOA first-order sea echoes, and the phase errors in array are estimated by minimizing the cost function through an iterative procedure. For phase error calibration, the MU method and the ML approach have already been compared in the previous work [18], and that work indicates that the MU method is better than the ML approach for the MHF radar. Therefore, the MU method is adopted for comparison in this paper.…”

“…In contrast, the WavE RAdar (WERA), which takes advantage of a long receiving array, adopts the beam-forming method to steer in the desired direction. However, in practical situations, both of the approaches are negatively affected by array uncertainties [18]. Without array calibration, the beam-forming method may result in an incorrect beam with a broadened beamwidth, and the direction-finding approach would yield a spurious direction with a poor angular resolution [19][20][21].…”

“…Subsequently, Flores-Vidal et al employed a number of unknown ship echoes to solve the phase errors from a cost function [27]. Recently, Chen et al developed an approach that is based on the MUSIC algorithm (so-called MU method) for calibrating phase errors while using single-DOA sea echoes [28], and this method was compared with the ML-based method based on current measurements [18]. Almost all of the aforementioned methods only consider the phase uncertainty for each receiving element as a constant value that does not vary with direction.…”

Validation of Sensing Ocean Surface Currents Using Multi-Frequency HF Radar Based on a Circular Receiving Array

“…For a phased direction-finding HF radar system, array phase uncertainties significantly degrade the performance of estimating the azimuth of the current signal. In this paper, an auto-calibration method is utilized to estimate Φ to calibrate the array signals before estimating the current maps [31,32]. As shown in Equation (6), the number of disparate sources M must be accurately estimated before using Equation (6) to determine the DOAs of current signals.…”

Improved Amplitude-Phase Calibration Method of Nonlinear Array for Wide-Beam High-Frequency Surface Wave Radar

“…Similar to the ML method, Chen et al proposed another appoach based on the multiple signal classification (MU) algotithm for amplitude and phase calibration using the reception matrices of single DOA sources [20]. Later, Zhao Chen validated and compared the ML method and the MU method, and the results showed that both methods can effectively improve the accuracy of ocean current estimation [21].…”