光探測與測距（光達）是一種光學遙感技術，通過計算反射發射光的飛行時間（TOF）來檢測物體的距離。 它可以通過計算雷射光在環境中傳播的延遲時間和光速來獲得深度信息。 然而，它很容易受到環境和其他光達系統的干擾和乾擾。而混沌光達是一種以混沌雷射光為光源，產生類噪聲的連續雷射光。並透過計算間接飛行時間（ITOF）、也就是通過計算發射信號和接收信號的互相關來獲得距離資訊。 混沌光達系統得益於混沌訊號的隨機性，其具有非常好的抗干擾能力、高精度、高分辨率以及好的能源使用效率。 然而，傳統的混沌光達系統是採用複雜且對環境敏感的光學系統作為混沌光源，這使得它們無法便攜和小型化。 因此，本研究提出了一種新型的數位混沌光達系統，它採用數位的方式來替代繁複的光學架構。
本研究將在現場可程式化邏輯閘陣列（FPGA）上實現混沌訊號產生器以產生混沌信號，而混沌訊號產生器是由混沌亂數產生器（CRNG）和處理單元所組成的。 混沌亂數產生器是透過解出混沌系統的解來獲取亂數的亂數產生器。本研究是採用洛倫茲系統(Lorenz system)作為混沌源，並通過一個稱為歐拉法(Euler method)的低複雜度數值分析對其進行求解，以生成亂數。 此外，本研究還引入了 Box-Muller 演算法作為後處理方法，對來自混沌亂數產生器的亂數進行後處理產生混沌訊號，以實現更高的吞吐量(throughput)和更好的抗干擾能力。 最後，透過將混沌訊號產生器產生的混沌訊號通過估計出的光達系統做檢測，評估其抗干擾能力。
本研究所提出的混沌亂數產生器可以生成非週期性、不相關的寬帶混沌信號，可以通過 NIST 檢測。 而經過後處理後，混沌信號保持了原有優勢，並提高了吞吐量以及更好的抗干擾能力。 而且，經過後處理的訊號有著可以匹配高斯白噪聲的抗干擾能力。 最後，本設計在 Xilinx VC707 FPGA上進行硬體實現。 在 100 MHz 工作頻率下混沌亂數產生器的亂數吞吐量可以達到 3 Gbits/s（1.5 M samples/s），而經過後處理的混沌訊號產生器的混沌訊號吞吐量可以達到 4.2 Gbits/s（3 M samples/s）。 本研究所提出的設計實現了一個高吞吐量和低硬體成本的數位混沌光源來取代現有複雜的光學系統，為未來高幀率和高分辨率的實時光達系統提供了更有效的解決方案。

Light Detection and Ranging (LiDAR) is a remote sensing technology that detects the object's distance by calculating the time-of-flight (TOF) of the reflected transmitting light. It can obtain depth information by calculating the delay time of laser light traveling through the environment and the speed of light. Nevertheless, it is vulnerable to interference and jamming from the environment and other LiDAR systems. Chaos LiDAR is a category of LiDAR which uses the chaos laser as the light source to generate a noise-like continuous wave. The chaos LiDAR system is based on the indirect time of flight (ITOF), in which the distance is obtained by calculating the cross-correlation of the transmitted and received signals. The chaos LiDAR system benefits from the randomness of chaos signals, which makes it possess outstanding anti-interference and anti-jamming capabilities, high accuracy and resolution, and energy efficiency. However, the conventional chaos LiDAR systems employ complex and sensitive optical structures as sources to generate chaos light, which makes them unable to be portable and miniaturized. Thus, this study proposed a new type of digital chaos LiDAR system, which uses a digital approach to replace the bulky optical chaos light source.
This study implemented a chaos signal generator on the field-programmable gate array (FPGA) to generate chaos signals, while the chaos signal generator comprises a chaos random number generator (CRNG) and processing units. CRNG is a variety of random number generators which solve the chaos system to acquire random signals. This study adopted the Lorenz system as the chaos source and solved it through a low-complexity numerical analysis called the Euler method to generate chaos signals. Furthermore, this study also introduced the Box-Muller algorithm as a post-processing method that operates on the chaos signal from CRNG to achieve higher throughput and better performance for system realization. At last, the generated signal from the chaos signal generator was evaluated through the estimated LiDAR system to see its performance.
The proposed CRNG can generate aperiodic, uncorrelated, and broadband chaos signals that can pass the NIST test. While after post-processing, the chaos signal maintains the advantages, improves the throughput, and becomes unpredictable. Moreover, the post-processed signal can match the anti-interference ability of the white Gaussian noise. Finally, the proposed design has been implemented on the Xilinx VC707 board. The throughput of the CRNG can achieve 3 Gbits/s (1.5 M samples/s), and the throughput with post-processing can achieve 4.2 Gbits/s (3 M samples/s) at 100 MHz operating frequency. The proposed design provides high throughput and low-cost hardware effort to replace the complicated optical system, paving the way for future high-speed and high-resolution real-time LiDAR systems.

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