Name
Title | ||
|---|---|---|
An Improved Method for Spot Position Detection of a Laser Tracking and Positioning System Based on a Four-Quadrant Detector. |
Abstract | ||
|---|---|---|
For the laser tracking and positioning system of a moving target using a four-quadrant detector, the accuracy of laser spot position detection has a serious impact on the tracking performance of the system. For moving target tracking, the traditional spot position detection method of a four-quadrant detector cannot give better consideration to both detection accuracy and operation speed. In view of this, an improved method based on piecewise low-order polynomial least squares fitting and a Kalman filter is proposed. Firstly, the tracking and positioning mathematical model of the system is created, and the experimental device is established. Then, the shortcomings of traditional methods are analyzed, and the improved method and the real-time tracking and positioning algorithm of the system are studied. Finally, through the experiment, the system operation effects are compared and analyzed before and after the improvement. The experimental results of system dynamic tracking show that, the least squares fitting of the experimental data using a 5-segment and quadratic polynomial can achieve better results. By using the improved method, the maximum tracking distance of a moving object is increased from 12 m to more than 30 m. At a distance of 7.5 m, the maximum tracking speed can reach 2.11 m/s, and the root mean square error (RMSE) of the position is less than 4.59 mm. At 15.5 m, the maximum tracking speed is 2.04 m/s and the RMSE is less than 5.42 mm. Additionally, at 23.5 m, it is 1.13 m/s and 5.71 mm. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.3390/s19214722 | SENSORS |
Keywords | Field | DocType |
laser tracking and positioning,four-quadrant detector,piecewise low-order 18 polynomial fitting,Kalman filter | Least squares,Computer vision,Mean squared error,Kalman filter,Electronic engineering,Quadratic function,Artificial intelligence,Engineering,Detector,Piecewise,Polynomial least squares,Positioning system | Journal |
Volume | Issue | ISSN |
19 | 21 | 1424-8220 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Wugang Zhang | 1 | 0 | 0.68 |
| Wei Guo | 2 | 442 | 146.38 |
| Chuanwei Zhang | 3 | 1 | 1.73 |
| Shuanfeng Zhao | 4 | 0 | 0.34 |