基于路網(wǎng)特征的慣性導(dǎo)航輔助定位算法的研究與實(shí)現(xiàn)
發(fā)布時(shí)間：2018-10-09 19:40
【摘要】：隨著社會(huì)經(jīng)濟(jì)的發(fā)展與科技水平的提高，慣性導(dǎo)航系統(tǒng)成為了社會(huì)經(jīng)濟(jì)發(fā)展和國防建設(shè)中必不可少的部分，并廣泛應(yīng)用于各個(gè)領(lǐng)域。但是慣性導(dǎo)航系統(tǒng)的定位誤差會(huì)隨著載體運(yùn)行時(shí)間的增加而累積，嚴(yán)重影響了定位的精度。為了解決這一問題，本文針對(duì)基于路網(wǎng)特征的慣性導(dǎo)航輔助定位算法展開研究，通過比較慣導(dǎo)軌跡與路網(wǎng)數(shù)據(jù)之間的特征差異，尋找兩者間的平移向量，并完成對(duì)定位點(diǎn)的位置修正。 本文的主要研究?jī)?nèi)容和完成的工作如下： 1、分析了慣性導(dǎo)航系統(tǒng)以及輔助定位技術(shù)的研究現(xiàn)狀和存在的問題，，指出采用路網(wǎng)數(shù)據(jù)輔助慣性導(dǎo)航定位的重要意義。給出了應(yīng)用于嵌入式或移動(dòng)載體的基于曲線特征的輔助定位系統(tǒng)的基本框架及各部分的功能，指出在輔助定位系統(tǒng)中，匹配算法是整個(gè)系統(tǒng)的核心。對(duì)現(xiàn)有的基于路網(wǎng)特征的輔助定位算法進(jìn)行了分析，指出其普遍存在的問題是在慣性導(dǎo)航系統(tǒng)的累積定位誤差較大的情況下無法達(dá)到良好的匹配效果。 2、基于路網(wǎng)特征的慣性導(dǎo)航輔助定位算法的研究基礎(chǔ)是路網(wǎng)數(shù)據(jù)，因此路網(wǎng)數(shù)據(jù)是整個(gè)算法的關(guān)鍵。文中分析了路網(wǎng)的結(jié)構(gòu)特點(diǎn)，建立了路網(wǎng)數(shù)據(jù)的空間索引、拓?fù)潢P(guān)系，按照標(biāo)準(zhǔn)格網(wǎng)索引和圖形拓?fù)潢P(guān)系，提出了采用二進(jìn)制文件的方式，以索引文件和路網(wǎng)數(shù)據(jù)文件對(duì)路網(wǎng)數(shù)據(jù)進(jìn)行存儲(chǔ)，并按照該存儲(chǔ)方式實(shí)現(xiàn)了數(shù)據(jù)讀取；分析了數(shù)據(jù)當(dāng)前壓縮算法的不足，針對(duì)存在的冗余和無效數(shù)據(jù)，設(shè)計(jì)了基于斜率的數(shù)據(jù)壓縮化簡(jiǎn)方法，并提出了慣導(dǎo)數(shù)據(jù)濾波的基本原則，實(shí)現(xiàn)了數(shù)據(jù)的預(yù)處理。 3、本文針對(duì)慣導(dǎo)累積定位誤差較大的問題，提出一種基于路網(wǎng)特征的慣性導(dǎo)航輔助定位算法。特征提取是整個(gè)算法運(yùn)轉(zhuǎn)的核心，文中設(shè)計(jì)了一種用于基于行駛狀態(tài)與子狀態(tài)共同判定的曲線特征提取模型，針對(duì)不同形狀特征的復(fù)雜道路進(jìn)行特征段的提取，具有較好的適應(yīng)性和較高的提取效率。同時(shí)設(shè)計(jì)了從路網(wǎng)數(shù)據(jù)和慣導(dǎo)軌跡進(jìn)行特征提取、特征最小外界矩陣計(jì)算、投影點(diǎn)判斷、平移向量的解算直到最后通過迭代誤差修正的具體算法流程，有效地抑制了慣導(dǎo)誤差的發(fā)散，適用于嵌入式環(huán)境下慣性導(dǎo)航的定位誤差修正。 4、論文最后利用Microsoft visual C++6.0開發(fā)環(huán)境完成了基于路網(wǎng)數(shù)據(jù)的輔助定位算法的實(shí)現(xiàn)，設(shè)計(jì)了算法的總體功能架構(gòu)，以及整體算法的基本流程，主要針對(duì)算法中數(shù)據(jù)讀取、曲線特征提取以及軌跡匹配與誤差修正等功能進(jìn)行相應(yīng)的實(shí)驗(yàn)驗(yàn)證。通過對(duì)實(shí)驗(yàn)結(jié)果的分析，表明該算法對(duì)慣導(dǎo)定位誤差的修正有良好的效果，具有較高的應(yīng)用價(jià)值。
[Abstract]:With the development of social economy and the improvement of science and technology, inertial navigation system has become an indispensable part of social economic development and national defense construction, and has been widely used in various fields. However, the positioning error of inertial navigation system will accumulate with the increase of carrier running time, which seriously affects the positioning accuracy. In order to solve this problem, this paper studies the inertial navigation aided positioning algorithm based on road network features, and finds out the translation vector between inertial navigation track and road network data by comparing the characteristics between the inertial navigation track and road network data. And complete the position correction of the positioning point. The main contents and work of this paper are as follows: 1. The research status and problems of inertial navigation system and auxiliary positioning technology are analyzed, and the significance of using road network data to assist inertial navigation positioning is pointed out. In this paper, the basic framework and the functions of the auxiliary positioning system based on curve feature for embedded or mobile carrier are given. It is pointed out that the matching algorithm is the core of the whole system in the auxiliary positioning system. This paper analyzes the existing auxiliary location algorithms based on road network features, and points out that the common problem is that the inertial navigation system can not achieve a good matching effect when the cumulative positioning error is large. 2. The research of inertial navigation aided location algorithm based on road network features is based on road network data, so road network data is the key of the whole algorithm. In this paper, the structural characteristics of road network are analyzed, and the spatial index and topological relation of road network data are established. According to the standard grid index and graph topological relation, the way of using binary file is put forward. The index file and road network data file are used to store the road network data, and the data reading is realized according to the storage mode, and the deficiency of the current data compression algorithm is analyzed, aiming at the redundant and invalid data. The method of data compression and simplification based on slope is designed, and the basic principle of inertial navigation data filtering is put forward, and the preprocessing of data is realized. 3. Aiming at the problem that the cumulative positioning error of inertial navigation is large, this paper presents an aided positioning algorithm for inertial navigation based on road network features. Feature extraction is the core of the whole algorithm. In this paper, a curve feature extraction model based on driving state and sub-state is designed, and the feature segment is extracted for complex road with different shape features. It has better adaptability and higher extraction efficiency. At the same time, the algorithm flow of feature extraction from road network data and inertial navigation track, calculation of feature minimum external matrix, judgement of projection point, calculation of translation vector, and final correction by iterative error are designed. It can effectively restrain the divergence of inertial navigation error and is suitable for the positioning error correction of inertial navigation in embedded environment. Finally, using Microsoft visual C 6.0 development environment, the paper completes the realization of the auxiliary positioning algorithm based on the road network data, designs the overall functional structure of the algorithm and the basic flow of the whole algorithm, mainly aiming at the data reading in the algorithm. The functions of curve feature extraction, trajectory matching and error correction are verified by experiments. Through the analysis of the experimental results, it is shown that the algorithm has a good effect on the correction of the inertial navigation positioning error, and has a higher application value.
【學(xué)位授予單位】：解放軍信息工程大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2013
【分類號(hào)】：U495;P227.9
本文編號(hào)：2260540
[Abstract]:With the development of social economy and the improvement of science and technology, inertial navigation system has become an indispensable part of social economic development and national defense construction, and has been widely used in various fields. However, the positioning error of inertial navigation system will accumulate with the increase of carrier running time, which seriously affects the positioning accuracy. In order to solve this problem, this paper studies the inertial navigation aided positioning algorithm based on road network features, and finds out the translation vector between inertial navigation track and road network data by comparing the characteristics between the inertial navigation track and road network data. And complete the position correction of the positioning point. The main contents and work of this paper are as follows: 1. The research status and problems of inertial navigation system and auxiliary positioning technology are analyzed, and the significance of using road network data to assist inertial navigation positioning is pointed out. In this paper, the basic framework and the functions of the auxiliary positioning system based on curve feature for embedded or mobile carrier are given. It is pointed out that the matching algorithm is the core of the whole system in the auxiliary positioning system. This paper analyzes the existing auxiliary location algorithms based on road network features, and points out that the common problem is that the inertial navigation system can not achieve a good matching effect when the cumulative positioning error is large. 2. The research of inertial navigation aided location algorithm based on road network features is based on road network data, so road network data is the key of the whole algorithm. In this paper, the structural characteristics of road network are analyzed, and the spatial index and topological relation of road network data are established. According to the standard grid index and graph topological relation, the way of using binary file is put forward. The index file and road network data file are used to store the road network data, and the data reading is realized according to the storage mode, and the deficiency of the current data compression algorithm is analyzed, aiming at the redundant and invalid data. The method of data compression and simplification based on slope is designed, and the basic principle of inertial navigation data filtering is put forward, and the preprocessing of data is realized. 3. Aiming at the problem that the cumulative positioning error of inertial navigation is large, this paper presents an aided positioning algorithm for inertial navigation based on road network features. Feature extraction is the core of the whole algorithm. In this paper, a curve feature extraction model based on driving state and sub-state is designed, and the feature segment is extracted for complex road with different shape features. It has better adaptability and higher extraction efficiency. At the same time, the algorithm flow of feature extraction from road network data and inertial navigation track, calculation of feature minimum external matrix, judgement of projection point, calculation of translation vector, and final correction by iterative error are designed. It can effectively restrain the divergence of inertial navigation error and is suitable for the positioning error correction of inertial navigation in embedded environment. Finally, using Microsoft visual C 6.0 development environment, the paper completes the realization of the auxiliary positioning algorithm based on the road network data, designs the overall functional structure of the algorithm and the basic flow of the whole algorithm, mainly aiming at the data reading in the algorithm. The functions of curve feature extraction, trajectory matching and error correction are verified by experiments. Through the analysis of the experimental results, it is shown that the algorithm has a good effect on the correction of the inertial navigation positioning error, and has a higher application value.
【學(xué)位授予單位】：解放軍信息工程大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2013
【分類號(hào)】：U495;P227.9
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本文編號(hào)：2260540
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