光達是一種測量目標距離或深度訊息的技術。我們可以通過估計光信號從設備傳輸到目標的時間來計算到目標的距離。由於我們在混沌光達系統中使用的光源是混沌光，它是一種類噪聲信號，因此該系統被稱為混沌光達系統。
混沌光達系統可以應用於各個領域，包括深度計算、自動駕駛、3D 建模、擴增時實境、虛擬實境等等。為了保證混沌光達系統的可靠性和有效性，實時光達系統勢在必行。本文介紹了在現場可程式化邏輯閘陣列和個人電腦上的混沌光達實時實現，以及研究過程中遇到的挑戰，例如光學儀器之間延遲、跨時脈域訊號處理等等，並且建立了圖形使用者介面，說明了以上問題的解決方案和演示結果並與現有的產品進行比較。以每秒 11 萬像素的吞吐量，混沌光達系統每秒提供 10 幀長100點寬100點深度分辨率，並且具有毫米等級的精準度。

Light detection and ranging (LiDAR) is a technique that measures the distance or depth information of the target. We can calculate the distance of the target by estimating the time of the transmission signal transmitting from device to target. Since the light source we use in the chaos LiDAR system is chaos laser, which is a noise-like signal, the system is called chaos LiDAR system. Chaos LiDAR system can be applied to various fields, including depth calculation, autopilot, 3D modeling, augmented reality, virtual reality, etc. To ensure the reliability and validity of chaos LiDAR system, an access to real-time LiDAR system is imperative. This thesis introduces the chaos LiDAR real-time implementation on field programmable gate array (FPGA) and personal computer (PC), followed by challenges during the research process, solutions to the problems and the demo results. With a throughput of 110 thousand pixels per second, the chaos LiDAR system provides 10 frames of 100x100 depth map resolution per second.

1 Introduction
1.1 Chaos LiDAR................................. 2
1.2 Research motivation............................. 5
1.3 Organization of This Thesis......................... 6

2 Depth Map Sensing of Chaos LiDAR
2.1 Time of Flight (ToF) technology....................... 9
2.2 Correlation of Reference and Target Signals................ 10
2.3 Interpolation Algorithm........................... 12
2.3.1 Interpolation Complexity Reduction................. 16

3 Implementation of Real-Time Chaos LiDAR System
3.1 Experiment Device.............................. 19
3.2 Chaos LiDAR System Diagram....................... 23
3.3 Hardware Block Diagram of Chaos LiDAR system............. 25
3.4 Chaos LiDAR Control Flow......................... 27
3.5 Hardware Design of depth-sensing Algorithm................ 33
3.6 FPGA placement problem.......................... 38
3.7 Software and Graphical User Interface (GUI)................ 41

4 Demonstrations of System and Results

5 Conclusion and Future Work
5.1 Conclusion................................... 53
5.2 Future Work.................................. 54

References 55

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