Applications of Cell-Ratio Constant False-Alarm Rate Method in Coherent Doppler Wind Lidar

Hao Zhu,Lingbing Bu,Wentao Zhang,Xingyou Huang,Haiyang Gao

doi:10.3390/atmos7120165

Abstract

A cell-ratio constant false-alarm rate (CR-CFAR) method for detecting the Doppler frequency shift is proposed to improve the accuracy of velocity measured by coherent Doppler wind lidar (CWL) in low signal-to-noise ratio (SNR) environments. The method analyzes the spectrum to solve issues of weak signal submergence in noise encountered in the widely used periodogram method. This characteristic is that the signal region slope is larger than the noise region slope in the frequency spectrum. We combined the ratio and CFAR to propose the CR-CFAR method. The peak area is discriminated from the spectrum using this method. By removing background noise, the peak signal is obtained along with the Doppler shift. To verify the CR-CFAR method, a campaign experiment using both CWL and a commercial Doppler lidar was performed in Hami, China (42°32′ N, 94°03′ E) during 1–7 June 2016. The results showed that the proposed method significantly improved the reliability of CWL data under low SNR conditions. The height—at which both horizontal wind speed correlativity and horizontal wind direction correlativity exceeded 0.99—increased by 65 m. The relative deviation of the horizontal wind speed at 120 m decreased from 40.37% to 11.04%. We used the CR-CFAR method to analyze continuous data. A greater number of wind field characteristics were obtained during observation compared to those obtained using the common wind field inversion method.

Highlights

The wind field is the direct consequence of wind energy resources
Considering wind field detection requirements, we developed a 50-m blind-area coherent Doppler wind lidar with an adjustable height ranging from 50 m to 290 m
To verify the application of cell-ratio constant false-alarm rate (CR-CFAR) in coherent Doppler wind lidar (CWL), an observation experiment was performed from 1 June to 7 June 2016 using the proposed CWL and a commercial lidar

Summary

Introduction

The wind field is the direct consequence of wind energy resources. Wind field resource assessment is critical for optimizing wind turbine parameters. Wind field evaluations are predominantly based on wind tower data. Measurement from the wind tower is relatively accurate and has been recognized as an industry standard. Wind towers require considerable labor and material resources for regular maintenance. If wind resources near a wind turbine are individually assessed by a wind tower in a wind plant, long test cycles and low testing efficiencies are unavoidable [1,2,3]

Methods

Results

Conclusion