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1、南京航空航天大学 硕士学位论文 GPS/SINS组合导航系统及其滤波算法研究 姓名：周晶 申请学位级别：硕士 专业：通信与信息系统 指导教师：黄显高 20081201 南京航空航天大学硕士学位论文 I 摘 要 近年来全球定位系统GPS和捷联惯导系统SINS的组合导航系统已经普遍应用于 导航领域并且得到充分发展为了提高导航系统的定位精度和抗干扰能力论文对 GPS/SINS 组合导航系统进行了研究并且着重探讨了其中的滤波算法尽管常规卡尔曼滤波算法在组合 导航中得到广泛使用但它对系统模型和噪声统计特性要求较高为解决这个问题作者相继 对自适应滤波 鲁棒滤波以及模糊理论等技术做了深入研究 并将它们应用到
2、组合导航系统中 论文主要工作如下 1论文在对 SINS 和 GPS 分别研究的基础上建立了 GPS/SINS 组合导航系统的数学模型 完成了组合导航系统中卡尔曼滤波器的设计通过仿真实现了 SINS 和 GPS 的组合导航 2针对常规卡尔曼滤波的不足论文将简化的 Sage-Husa 自适应滤波算法和衰减因子自适 应算法相结合提出了一种改进的自适应算法利用此算法对组合导航系统进行了仿真结果 表明改进的算法解决既能保证滤波的精度又能保证滤波的稳定性 3论文阐述了H?滤波理论并利用H?滤波算法具有鲁棒性的优点将它用于 GPS/SINS 组合导航系统中仿真中设计了有色噪声以及系统模型参数存在误差两种环境
3、在此环境下和 传统卡尔曼滤波器进行滤波性能比较结果表明H?算法能够解决噪声统计特性和模型参数不 易确定的问题有效地克服了卡尔曼滤波的缺点 4 论文将模糊理论与卡尔曼滤波相结合 提出了一种基于模糊理论在线自适应改变量测噪 声方差阵的算法在此算法中设计了一种自适应滤波器它通过对残差的各个分量进行观测 应用多个模糊推理系统对量测噪声方差阵进行修正使其逐渐逼近真实噪声特性仿真结果表 明该算法能够很好地适应噪声变化提高了导航精度 关键词关键词 组合导航GPS/SINS卡尔曼滤波自适应滤波H?滤波模糊逻辑 GPS/SINS 组合导航系统及其滤波算法研究 II Abstract Recently, the
4、GPS/SINS integrated navigation system has been applied in navigation fields widely and become a leading trend of navigation technology. In order to achieve high guidance -precision and anti-jamming, this paper focuses on the filtering algorithms in GPS/SINS integrated system. Though the common Kalma
5、n algorithm has been used widely, its limit is that the algorithm must acquire the exact system model and the statistical nature of the noise. To solve this problem, the adaptive filtering, robust filtering and fuzzy logic is researched deeply and we apply these techniques in the integrated navigati
6、on system. The main tasks are as follows: 1. Based on the research of GPS and SINS separately, the system model of GPS/SINS is established and the Kalman filter for this system is also designed. We carry a simulation for this system and the results indicate the integrated navigation has been achieve
7、d. 2. We developed an improved Sage-Husa adaptive filtering algorithm which combines the simplified Sage-Husa adaptive filtering and adaptive fading filtering. Applying this algorithm in GPS/SINS and simulation results illustrate the improved algorithm can assure both the precision and stability of
8、the navigation system. 3. The H? filter theory is expatiated, then we take advantage of the H? algorithms robustness and apply this algorithm in GPS/SINS. According to the simulation under conditions of colored noise and deviation in system model, we conclude the H? algorithm resolve the problem tha
9、t either the system model or the statistical nature of noise is hardly to determine, so it overcomes the weakness of common Kalman filter effectively. 4. We proposes an adaptive algorithm which can online adjust the measuring noise covariance matrix R based on fuzzy theory. An adaptive filter is des
10、igned int this algorithm and it can modify the matrix R through multiple fuzzy inference systems by monitoring every element of residual, so that it makes the covariance approach the real measuring noise covariance gradually. The simulation results indicate it has a superiority of adapting noise var
11、iation and may greatly improve the precision of the navigation system. Keywords: integrated navigation, GPS/SINS, Kalman filter, adaptive filter, H? filter, fuzzy logic GPS/SINS 组合导航系统及其滤波算法研究 VI 图 表 清 单 图 2.1 捷联惯导系统原理图.8 图 2.2 捷联惯导系统程序编排.13 图 2.3 捷联惯导系统仿真原理图.16 图 2.4 陀螺仪仿真器.17 图 2.5 加速度计仿真器.17 图 2.6 SINS 东向速度误差.18 图 2.7 SINS 北向速度误差.18 图 2.8 SINS 经度误差.18 图 2.9 SINS 纬度误差.18 图 2.10 SINS 航向角误差.19 图 2.11 SINS 俯仰角误差.19 图 2.12 SINS 翻滚角误差.19 图 2.13 GPS 定位原理 .20 图 3.1 位置-速度组合方式 .24 图 3.2 伪距-伪速率组合方式 .
