Interpolation Algorithms for High-Accuracy Chaos Lidar
Jun-Da Chen1*, Chih-Hao Cheng1, Fan-Yi Lin1
1Institute of photonics technologies, National Tsing Hua University, Hsinchu, Taiwan
* Presenter:Jun-Da Chen, email:mmmevery@gmail.com
We developed two new interpolation algorithms, Subsample Waveform Shifting (SWS) and Subsample Cross-Correlation (SCC), to enhance the accuracy of a chaos lidar system. A chaos lidar system calculates the cross-correlation function of a backscattered signal and a reference signal to obtain the time-of-flight and thus the target distance. The accuracy of the chaos lidar is directly determined by the sampling frequency of the analog-to-digital converter (ADC). To enhance the accuracy, interpolation algorithms specially designed for the chaos signals are of interests. The SWS developed uses the correlation trace from a known location as the model. Transferring the model into the frequency domain by Fourier transform, continuous phase adjustment can be performed to find the exact location which the correlation trace of an unknown location and the model are most similar. For the SCC, on the other hand, it finds the exact location by shifting the delay between the reference signal and the backscattered signal with a subsample increment. In this study, the performance of the SWS, SCC, and other conventional interpolation algorithms under different operating conditions, such as optical intensity, correlation length, bandwidth and sampling frequency, are discussed. With a sampling frequency of 1.25 GS/s, the accuracy of the chaos lidar system are shown to be improved from 3.47 cm to 0.05 cm by employing the SWS or SCC interpolations.


Keywords: Chaos lidar, Interpolation , Accuracy, Cross-correlation, Range finding