本文選題：慣性導(dǎo)航系統(tǒng) + 卡爾曼濾波��； 參考：《電子科技大學(xué)》2014年碩士論文

【摘要】：隨著技術(shù)的進(jìn)步,原本應(yīng)用于軍事領(lǐng)域的各種導(dǎo)航技術(shù)已應(yīng)用于民用領(lǐng)域或正在向民用領(lǐng)域推廣。在民用領(lǐng)域,導(dǎo)航系統(tǒng)的安全性至關(guān)重要,完好性作為對(duì)導(dǎo)航系統(tǒng)安全性的一種衡量是評(píng)價(jià)一個(gè)導(dǎo)航系統(tǒng)優(yōu)劣的重要標(biāo)準(zhǔn)。自主導(dǎo)航是一種不借助人工設(shè)置的目標(biāo)和信息源的導(dǎo)航儀器來(lái)引導(dǎo)物體運(yùn)行的導(dǎo)航方法,慣性導(dǎo)航就是一種自主導(dǎo)航,包含慣性導(dǎo)航的組合導(dǎo)航也可以歸于自主導(dǎo)航。導(dǎo)航系統(tǒng)需要獲得測(cè)量信息進(jìn)行導(dǎo)航解算,本文將重點(diǎn)研究如何通過(guò)故障檢測(cè)來(lái)提高導(dǎo)航系統(tǒng)的完好性。首先,對(duì)慣性導(dǎo)航系統(tǒng)進(jìn)行仿真分析。慣性導(dǎo)航系統(tǒng)為了確定運(yùn)動(dòng)物體的初始姿態(tài)要先進(jìn)行初始對(duì)準(zhǔn)。初始對(duì)準(zhǔn)包括粗對(duì)準(zhǔn)和精對(duì)準(zhǔn),精對(duì)準(zhǔn)用卡爾曼濾波器估計(jì)粗對(duì)準(zhǔn)的誤差。本文提出了改進(jìn)的精對(duì)準(zhǔn)算法,利用兩個(gè)加速度計(jì)的輸出和陀螺儀的三個(gè)輸出共五個(gè)值作為卡爾曼濾波器的觀測(cè)值。建立數(shù)學(xué)模型模擬陀螺儀和加速度計(jì)的輸出,并搭建了慣性導(dǎo)航系統(tǒng)仿真平臺(tái),對(duì)改進(jìn)的精對(duì)準(zhǔn)進(jìn)行了仿真分析。仿真結(jié)果顯示改進(jìn)的精對(duì)準(zhǔn)算法提高了對(duì)方位誤差角的估計(jì)精度。其次,仿真分析了GPS導(dǎo)航系統(tǒng),并在慣性導(dǎo)航系統(tǒng)平臺(tái)上結(jié)合GPS導(dǎo)航系統(tǒng),分別仿真松組合導(dǎo)航和緊組合導(dǎo)航,對(duì)不同導(dǎo)航系統(tǒng)的仿真結(jié)果進(jìn)行比較分析。搭建的仿真平臺(tái)為之后的故障檢測(cè)研究做鋪墊。然后,對(duì)故障檢測(cè)展開研究。首先介紹最優(yōu)奇偶矢量法,它是多故障檢測(cè)的基礎(chǔ),發(fā)現(xiàn)最優(yōu)奇偶矢量法存在缺陷,不同觀測(cè)值中的故障有可能使殘差變小,不利于對(duì)故障的檢測(cè)。為了解決這個(gè)問(wèn)題,本文提出了改進(jìn)的最優(yōu)奇偶矢量法,仿真比較傳統(tǒng)的方法和改進(jìn)的方法對(duì)故障的檢測(cè)效果,仿真結(jié)果表明改進(jìn)的最優(yōu)奇偶矢量法有效地解決了殘差變小的問(wèn)題。實(shí)際情況中觀測(cè)精度可能不同,仿真比較殘差標(biāo)準(zhǔn)化法和加權(quán)奇偶矢量法對(duì)故障的檢測(cè)效果,分析加權(quán)奇偶矢量法的優(yōu)勢(shì)。另外本文發(fā)現(xiàn),當(dāng)卡爾曼濾波器中待估值的個(gè)數(shù)遠(yuǎn)遠(yuǎn)大于觀測(cè)值的個(gè)數(shù)的時(shí)候,無(wú)法使用最優(yōu)奇偶矢量法檢測(cè)觀測(cè)方程中的故障,因此構(gòu)造新的統(tǒng)計(jì)量檢測(cè)其中的故障,仿真驗(yàn)證了新的統(tǒng)計(jì)量對(duì)故障具有較好的檢測(cè)效果。最后,研究在GPS和組合導(dǎo)航系統(tǒng)中引入故障檢測(cè)的方法和可行性。仿真驗(yàn)證了本文提出的故障檢測(cè)算法在這些導(dǎo)航系統(tǒng)中能有效地檢測(cè)出故障。
[Abstract]:With the development of technology, all kinds of navigation technology used in military field have been applied to civilian field or are being popularized to civilian field. In civil field, the security of navigation system is very important. As a measure of navigation system security, completeness is an important criterion to evaluate a navigation system. Autonomous navigation is a kind of navigation method which can guide the operation of objects without the aid of the navigation instrument of the target and information source. Inertial navigation is a kind of autonomous navigation, and the integrated navigation including inertial navigation can also be attributed to autonomous navigation. Navigation system needs to obtain measurement information for navigation solution. This paper will focus on how to improve the integrity of navigation system through fault detection. First, the inertial navigation system is simulated and analyzed. In order to determine the initial attitude of the moving object, the inertial navigation system needs initial alignment. The initial alignment consists of coarse alignment and fine alignment. Kalman filter is used to estimate the error of coarse alignment. In this paper, an improved precision alignment algorithm is proposed, which uses the output of two accelerometers and three outputs of gyroscopes as the observed values of Kalman filter. The mathematical model is established to simulate the output of gyroscope and accelerometer, and the simulation platform of inertial navigation system is built. The improved precision alignment is simulated and analyzed. Simulation results show that the improved precision alignment algorithm improves the precision of azimuth error angle estimation. Secondly, the GPS navigation system is simulated and analyzed, and the loose integrated navigation and compact integrated navigation are simulated on the inertial navigation system platform. The simulation results of different navigation systems are compared and analyzed. The simulation platform is used to pave the way for the later fault detection research. Then, the research on fault detection is carried out. This paper first introduces the optimal even-odd vector method, which is the basis of multi-fault detection. It is found that the optimal odd-even vector method has defects, and the fault in different observation values may make the residual error smaller, which is not conducive to fault detection. In order to solve this problem, an improved optimal even-odd vector method is proposed in this paper. The simulation results are compared with the traditional method and the improved method for fault detection. The simulation results show that the improved optimal even-odd vector method can effectively solve the problem of reducing the residual error. The actual observation accuracy may be different. The residual standardization method and the weighted odd-even vector method are compared in the fault detection effect, and the advantages of the weighted odd-even vector method are analyzed. In addition, it is found that when the number of Kalman filters to be estimated is far greater than the number of observed values, it is impossible to detect the faults in the observation equation by using the optimal even-odd vector method, so a new statistic is constructed to detect the faults. The simulation results show that the new statistic is effective for fault detection. Finally, the method and feasibility of introducing fault detection into GPS and integrated navigation system are studied. Simulation results show that the proposed fault detection algorithm can effectively detect faults in these navigation systems.
【學(xué)位授予單位】：電子科技大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類號(hào)】：TN96

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本文編號(hào)：2048125