Fast Phase Recognition of Mechanical Helical Phased Array Antenna Element Based on Line-Scan Machine Vision

Mechanical helical phased array antenna (HPAA) realizes microwave beam directing by mechanically rotating the helical antenna element. Measuring and calibrating the phase of the HPAA, which can be simplified to measure and calibrate the phase of each helical antenna element, is significantly important to evaluate the antenna performance. To realize fast phase measurement and calibration of element antenna, this article proposed a line-scan machine vision (MV) strategy. A prototype MV system combining a line-scan camera and a guide rail structure to acquire the image of the helical antenna element is designed and proposed. Phase recognition algorithm based on deep-learning you only look once v8 (YOLOv8) and pixel difference networks (PiDiNets) with field-of-view-error (FOVE) minimization is proposed to conduct element detection and edge detection and further to determine the angular state that quantifies the phase of the helical antenna element. Statistical analysis of experimental results on a
$5 \times 8$
test antenna array shows that ±1° phase recognition accuracy can be achieved within 43 s to demonstrate the accuracy and efficiency of our proposed method. Moreover, the measurement uncertainty of the proposed approach is analyzed that can be quantified with a normal distribution to show 83% of recognized result errors fall with 1° to demonstrate its stability and reliability.