Research On System Consistency And Optimal States Estimation Of LIDAR/INS Integrated Navigation System

Reasearchers have developed various of integrated navigation systems for large number of applications, which mainly designed with Inertial Navigation System as principal part. But systems using satelliates to aid INS suffer the problem of signal jamming and blocking. So independent integrated system, which sensing the environment to aid INS, are regarded as one potential solution. Compare to many kinds of senors, LIDAR(Light Detection and Ranging) is able to mapping 3D environment directly and accurately. So it is possible to integrate LIDAR and INS for precise navigation on military or civil area.In this dissertation, some key technologies of LIDAR/INS integrated system are offered, including consistency problem for 3D feateure detection, measurement consistency problem between LIDAR and INS system, global observability analysis and global steates estimation for integrated system. These four problems are tight parts for a whole. The main contributions include the following aspects:(1) The basic frame of integrated navigation is discussied, including measurements construction with three type landmarks, linearization model for filter, 3D points cloud transtition into key frame. Also the error source of integrated system is discussied. The analysis result indicates it is feasible to build the LIDAR aiding INS integetrated system.(2) Inorder to dectction regular landmarks such as patch or cylinder, the 3D Hough Transform is deeply analysed. For 3D case, the Hough Transform must divide the parameters on the spherical surface, but the Gaussian segmentation is only average on parameter space but not on sphere geodesic, which may cause singularity for patch's or cylinder's normal which point to high latitude area. If the singularity phenomena were appeared, the landmark detection is unconsistency. Then the dual segementation of sphere parameter is proposed to avoid the singularity phenomena, which divide the sphere into two approximate Gussian coordinates and define coordinates with different area and rotations. Based on dual segementation, the dual 3D Hough Transform can get complete and consistent segmentation for half sphere, then the landmark detection is nearly consistent for all area of sphere. The experiments show that dual 3D Hough Transform can dectect regular landmarks with arbitrary normal.(3) The dissertation discussed local interest point detector in points cloud with multi-scale consistency. The equivalence between Gaussian kernel on grid and the unorganized multi-scale geometry flow smoothing method is established. Based on multi-scale geometry flow smoothing, the interest point is detected with characteristic curvature, which is invariant to scale, rotation and transition. Also the descriptor of local curvature is proposed for points cloud matching. The experiment show that local interest point detector performs well in complicated environment.(4) The measurements consistency between LIDAR and INS is discussed, which also called calibration problem of integrated system. Firstly, the measurement geometry is proposed with control points and control area. Then the scan line correction algorithm is discussed for laser intensity image, which revise the raw control points to ground truth points. In order to slove the rotation matrix, the Wahba attitude determination alograthim is imported to estimate the matix with SO(3) restrict, which gets a global optimized result. The experiments using real LIDAR is implemented and the result shows that in large biases case, the algorithm can improve 6.71% accuracy than least squre method. Also with noise increase, the estimation is robust.(5) The newly theoretical analysis of nonlinear global observability of LIDAR/INS integrated system is propsed. Considering integrated system respectively with high precision INS and low precision INS, the dissertation gives the global observability conditions respectively for three types of landmarks. The result of observability extends the covariance anlyisis result of mutli-LOS(line of sight) observation and be more comprehensible than conventional conclusion. The observability analysis is straightforward and intuitionistic, which provide a theoretic fundation in designing the filter for integrated navigation. The simulation and experiments result shows that positioning accuracy of integrated navigation system is better than 5m, the attitude accuracy is better than 0.1o.(6) The hybrid estimation algorithm is propsed, which using global extended states to estimate both navigation states and landmark location. In conventional SLAM method, the location of landmarks can be estimated for revising the vehicle's postion. For that LIDAR is a popular senor in SLAM, it is worthful to import this mehod into LIDAR/INS integrated navigation. The convergence of landmark in integrated navigation is discussed. The result shows that convergence in SLAM is weakly but this weakly convergence can transfer to strong convergence when there be observations of absolute landmarks. Furthermore, the strong convergence of landmarks can lead the location of vehicle to strong convergence, which improves the total location accurary for full navigation process. The simulation result shows the hybrid algorithm performs better than pure SLAM and pure integrated navigation mehod. Key Words:Integrated Navigation; LIDAR(Light Detection Radar); Strapdown Inertial Navigation System; System Consistency; 3D Interest Points Detection; Attitude Determination; Nonlinear Global Observability; Global States Extend; Estimation Convergence...