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系統識別號 U0026-1808201413052900
論文名稱(中文) 慣性感測器發展與結合低成本導航器冷原子慣性量測元件模擬精度評估
論文名稱(英文) The Evaluation of Inertial Sensors and the Simulated Performance Evaluation of a Cold Atomic Interfered IMU Aided Low Cost Navigation Systems
校院名稱 成功大學
系所名稱(中) 測量及空間資訊學系
系所名稱(英) Department of Geomatics
學年度 102
學期 2
出版年 103
研究生(中文) 郭子暭
研究生(英文) Tzu-Hao Kuo
學號 P66014028
學位類別 碩士
語文別 英文
論文頁數 138頁
口試委員 指導教授-江凱偉
口試委員-陳國華
口試委員-韓仁毓
中文關鍵字 冷原子干涉儀  冷原子陀螺儀  冷原子加速度計  多慣性量測元件整合 
英文關鍵字 cold atomic interferometer  cold atomic gyroscope  cold atomic accelerometer  multiple IMU integration 
學科別分類
中文摘要 在1970年代,高精度的平台式的機械慣性感測器在無外在訊號支援情況下,已經可達100公尺等級的定位精度。然而這種類型的慣性感測器十分笨重、零件數眾多、組裝複雜、高耗能,再加上大量生產不易等情況下,其成本居高不下。然而,伴隨著精度只須符合應用層面的要求(例如: 應用於飛航的導航等級慣性感測器會整合其他較便宜的無線電接收機,因此毋須使用超高精度的慣性導航儀),且加上零件的精簡與新的材料、技術出現,慣性感測器的成本已可大幅降低。原子型慣性感測器是一種不需藉由任何外在訊號的輔助,憑著本身的偏差與隨機誤差即可達到10公尺以內的定位精度的一種新型導航元件,是目前最高精度的慣性導航儀。且在同高精度的要求下,它的成本可比傳統的平台式機械慣性感測器、光學感測器更為低廉。是一種極具發展前途的慣性導航元件。但是該類型的儀器目前仍處於研發階段,所以仍然有些問題存在。像是,體積較傳統的慣性感測器大、低取樣頻率與低運作範圍等缺點,阻礙原子慣性感測器在實務上的應用。

而本研究為了介紹冷原子慣性感測器這種新型儀器的運作原理、歷史回顧與相關應用,除了針對冷原子感測器的低取樣頻率與低動態範圍的問題作處理與開發相對應的整合演算法外,尚回顧目前傳統慣性感測器的發展歷程與基本運作原理,以期接軌冷原子慣性感測器與傳統慣性感測器。

本論文所採用的演算法,主要分為參考軌跡的模擬、慣性量測元件的觀測量產生與導航方程式的運作、全球定位系統的模擬,與慣性量測元件與全球定位系統的整合。慣性量測元件的整合包含冷原慣性感測器元件與傳統的微機電慣性感測器做整合,該整合之目的期許微機電慣性感測器可克服冷原子慣性慣測器的低取樣問題,並利用冷原子感測器的穩定性降低微機電慣性感測器的定位飄移。以本研究為例,該微機電慣性感測器1分鐘內的飄移誤差可達300~400公尺。另一整合是利用全球定位系統來控制冷原子慣性感測器因取樣不足所造成的定位誤差。然而,前面兩種整合方式主要針對克服冷原子慣性感測器的低取樣頻率。冷原子慣性感測器尚有低運作範圍問題,這會使到冷原子慣性感測器在高動態環境下無法運作,導致嚴重的定位誤差產生。此時一個整合冷原子慣性感測器、微機電慣性感測器與全球定位系統的系統便可藉由全球衛星系統輔助的微機電慣性感測器可在冷原子慣性感測器無法運作的情況下繼續導航。

並由以上方法可得知,冷原子感測器與微機電慣導元件的鬆耦合架構並不能藉由微機電慣導元件的高取樣頻率來彌補冷原子感測器所漏掉的動態細節。因為在鬆耦合的整合過程中,冷原子感測器所計算出的位置已存在因低取樣頻率所造成的誤差,所以該冷原子感測器的取樣誤差會回饋至微機電慣導元件中。使得雙慣性感測器系統的成果與純慣導的冷原子慣性導航元件差不多。全球衛星系統輔助的冷原子慣性感性測器在可接收衛星訊號時,不管是藉由位置更新、速度更新,還是位置與速度一起更新,皆可達到不錯之定位成果,在水平與高程方向之定位誤差約可控制於5公尺之內。此外,當量測協變方矩陣與狀態協變方矩陣設計得當時,卡曼濾波在全球衛星系統訊號不被接收的時段下,所估計的狀態仍可近似純慣導的冷原子慣性感測器在該時段下的狀態輸出。在微機電慣性感測器、冷原子慣性感測器與全球定位系統整合架構中實踐了,當衛星訊號被遮蔽時,原子感測器的觀測量仍可用來更新微機電慣導元件以降低該微機電慣性量測元件在獨立運作情況下所造成的定位誤差,其定位精度約略小於全球衛星系統輔助的冷原子慣性感性測器的定位精度。另一方面,當冷原子感測器不可運作時,衛星訊號仍可被用來更新微機電慣導元件以維持定位品質。不管衛星訊號是被屏蔽與否,在這三整合系統架構中,當整合微機電感測器時,其較低的儀器精度會使得誤差傳播到冷原子慣性感性測器與全球衛星系統整合系統促使整合解的精度較冷原子慣性感測器與全球定位系統整合架構低。話雖如此,卡曼濾波器的二階段更新尚可緩和不正確估計的量測協變方矩陣與狀態協變方矩陣所帶來錯誤狀態估計。
英文摘要 The highly accurate mechanized platform inertial sensors without any external aiding signals had already achieved the positioning accuracy of 100 m in 1970s. However, this type of inertial sensors is very bulky and power consumption. In addition, these inertial measurement units (IMUs) are complex in the batch fabrication due to multitudinous parts so the cost has been always high. Despite the expensive IMUs, the accuracy requirements only conform to the applications. For instance, the IMUs applied in the civil aviation don’t need the excellent accuracy for free inertial since the radio receivers are integrated with the IMUs. The new materials, reduction of components, and innovative techniques for the inertial sensors are able to decrease the cost as well. Cold atomic interfered (CAI) IMUs based on their bias stability and random walk can provide significantly improved positional accuracy (<10 m) than all current IMUs. Furthermore, the prices of CAI IMUs can be less expensive than current mechanized platform and optic inertial sensors on the demand of same accuracy. Nevertheless, whereas CAI IMUs are the underdevelopment techniques, they have some problems such as higher volume, lower sampling rate, and lower operation range, than traditional IMUs, obstructing practical applications.

In addition to the introduction of the operation principle, historical reviews, and related applications of CAI IMUs as well as the developed integration algorithms for the CAI IMU focusing on the problems of low operation range and low sampling rate, the developments and fundamental operation methods of famous conventional IMUs are also looked back in order to connect the relevance of inertial sensors in this research.

The adopted algorithms in this thesis include the generation of dynamic trajectories, measurement generation and the mechanization equations of inertial navigations, simulation of Global Positioning System (GPS), and the integration between the IMUs and GPS. The combination of dual IMUs (a micro electro mechanical system (MEMS) IMU and a CAI IMU) tries to utilize the high sampling rate of the MEMS IMU to assist the CAI IMU to capture detailed dynamics and restrain the positional drift caused by the MEMS IMU through the correction from the CAI IMU. The positional error of the MEMS IMU simulated in this research can achieve 300 m~400 m in one minute. The CAI IMU/GPS integration exploits GPS to reduce the positional error of the CAU IMU because of the inadequate sampling rate. Above two integrations only consider the problem of sampling rate. Nonetheless, the low operation range of CAI IMUs will produce serious positional error as the CAI IMUs are operated in high dynamic environment. The triple integration of a CAI IMU, a MEMS IMU, and GPS is capable of compensating the outages of the CAI IMU via the output of navigation solutions of the MEMS IMU aided with GPS.

According to aforementioned approaches, the integration between a CAI IMU and a MEMS IMU via loosely coupled scheme doesn’t have significant variation compared with free inertial CAI IMU since the states computed from the CAI IMU already containing sampling error will be fed back to the states of the MEMS IMU via updating. The GPS-aiding CAI IMU can reach good performances the horizontal and vertical accuracy of 5 m by the position, velocity, and position/velocity updating if no GPS outages. Apart from the case of no GPS outages, the estimated states of the CAI IMU/GPS is similar to the states of the unaided CAI IMU during the GPS outages supposing the measurement covariance matrix and system covariance matrix in the Kalman filter are proper for matching the conditions of the CAI IMU/GPS system. The programs of the triple system fulfill that the positional error aroused by the MEMS IMU can be controlled by the CAI IMU encountering the GPS outages and remained by the estimation of the MEMS IMU updated by GPS in CAI IMU outages. Whether the GPS outages take place or not, the positional accuracy of the triple system is a bit less than the CAI IMU/GPS system since the sensor error of the MEMS IMU will be propagated to the estimated states of the CAI IMU/GPS, too. Having said that, the two-stages updating in the Kalman filter can smooth the error fluctuation due to the incorrect estimation of the measurement noise variance matrix and the system noise variance matrix.
論文目次 中文摘要(Chinese Abstract)...I
Abstract...III
致謝(Chinese Acknowledgement) ...V
Contents...VI
List of Table...VIII
List of Figures...IX
Abbreviations...XII
Symbols...XIV
Chapter 1 Introduction...1
1.1 Research Background...1
1.2 Motivation and Objective...6
1.3 Overview of this Thesis...8
Chapter 2 Literature Review of Conventional Inertial Sensors...9
2.1 Historical Review of Gyroscopes...9
2.2 Historical Review of Accelerometers...19
2.3 Sagnac Effect on RLGs, IFOGs, and AIGs...26
2.4 Platform and Strapdown Inertial Sensors...33
2.5 IMU Integrated with Other Sensors...34
Chapter 3 Innovational Inertial Sensors: Cold Atomic Interferometry Inertial Sensors...36
3.1 Essential Structure and Theory of a CAI Sensor...36
3.2 Brief Overview of CAI Sensors...50
3.3 The Potentials of CAI Sensors...57
3.4 Related Applications...59
Chapter 4 Strategy of Multiple-Sensors Integration...62
4.1 Definition of Reference Frames and Transformations...62
4.2 Dynamic Trajectory Generation...67
4.3 Simulation of an Inertial Measurement Unit...70
4.4 Simulation of Global Positioning System...75
4.5 Integration Algorithm...91
Chapter 5 Results and Discussions...96
5.1 Test Environment: Dynamic Trajectory and Specifications of IMUs...97
5.2 The Navigation Results of the Unaided CAI IMU...100
5.3 Integration of a CAI IMU, a MEMS IMU, and GPS...105
Chapter 6 Conclusions and Recommendations of Future Researches...126
6.1 Conclusions...126
6.2 Recommendations of Future Researches...127
Reference...132
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