Yanling Hao

Comparison of Unscented Kalman Filters

Unscented Kalman filter (UKF) has been proven to be a superior alternative to the extended Kalman filter (EKF) when solving the nonlinear system in previous literatures. In order to accelerate the application of UKF in the actual system, a new simplified UKF is proposed in this paper. It is called Rao-Blackwellised additive unscented Kalman filter (RBAUKF), and is specially designed for the dynamic system with the additive noise, the nonlinear state equation and the linear measurement equation. Furthermore, three kinds of UKF are introduced at the same time for the purpose of comparing their advantage and disadvantage. The three filters are general UKF, additive unscented Kalman filter (AUKF), and Rao-Blackwellised unscented Kalman filter (RBUKF). In fact, the AUKF and RBUKF are the improved filters of the general UKF, and RBAUKF proposed in this paper is the upgraded version, which synthesizes the feature of AUKF and RBUKF. Finally, the simulation and analysis of the above UKF algorithms are done. The simulation results indicate that the computational complexity of RBAUKF is nearly half of UKF. The computational complexities of AUKF and RBUKF are in between UKF and RBAUKF. Moreover, the estimation accuracies of RBAUKF, AUKF and RBUKF are the same, while that of UKF is lower than theirs. It suggests that the performance of RBAUKF is best following by AUKF and RBUKF, and it is better than the general UKF.

Research on the dynamic error of strapdown inertial navigation system

Researching on the static error of strapdown inertial navigation system (SINS) plays a great role in the past. This is mainly due to the complex mathematical model for dynamic error of SINS. It is hard to do the error analysis from the perspective of the number. So in most cases, the static model owns the better position in the research for its desirable and concise. It is easy to know the impact to system error from three major error sources, and also the reasons of every periodic oscillation. However, the limitations of the static model drives the analysis for dynamic one to be more vital for the latter is consistent with actual situation. In this paper, the dynamic error model of SINS is established basing on the static one, then do the simulative research on error of some situations which the base is having a uniform motion. And give the explanation to results of simulations from the perspective of theory. It can lay the foundation for the research of dynamic error on multiple bases for the future movement.

Fuzzy adaptive Kalman filter for marine INS/GPS navigation

The integrated INS/GPS navigation system, which is applied to the marine, is necessary to provide long-term high accurate navigation information. A fuzzy adaptive Kalman filter (FAKF) is developed to estimate the navigational information accurately, and achieve the in-flight alignment and positioning. The proposed algorithm adaptively changes the corresponding weighted factor via fuzzy logic for every observable, and utilizes the weighted matrixes to adjust the Kalman filter. The weighted-matrixes come from four channels, which respectively respond to the residuals of latitude, longitude, east velocity and north velocity, in the fuzzy logic controller. The result of simulation and test shows perfect knowledge of the a prior information will be only of secondary importance when the estimator selects the FAKF to achieve integrated navigation, not conventional Kalman filter (CKF). In the case of insufficiently known a prior statistics, the in-flight alignment and positioning performance of FAKF is better than CKF, and FAKF is more efficient.

Path Planning for Aircraft Based on MAKLINK Graph Theory and Multi Colony Ant Algorithm

The task of path planning for aircraft has received considerable attention in the research literature. The problem involves computing a collision-free path between a start point and a target point in environment of known obstacles. In this paper, we investigate an obstacle avoidance path planning problem using the MAKLINK graph theory and multi ant colony system, in which several colonies of ants cooperate in finding optimal solution by exchanging good information. The result of computer simulation experiment shows that the proposed method is effective and can be used in the path planning of aircraft.

The Research and Application of Content-Based Satellite Cloud Image Retrieval

Content-based satellite cloud image retrieval is a very important problem in image processing and analysis field. Traditional image retrieval method has some limitation, for realized image retrieval accurately and quickly, the CBIR method is an adaptive method. For achieved good retrieval result, some of the pretreatment method of the satellite cloud image was used, and the experiment effect was shown. The basic theory and structure model of satellite cloud image database was studied systematically, and the data model of satellite cloud image database was provided. On the basis of studied the key technology of CBIR, we could obtain the better retrieval result, and the image retrieval result was shown in detail. At last, the application of CBIR method in satellite cloud image has been studied. The experiment result proves that the research and application of content-based satellite cloud image retrieval is valuable, which could improve the image search efficiency more.

Contented-based satellite cloud image processing and information retrieval

Satellite cloud image is a kind of useful image which includes abundant information, for acquired this information, the image processing and character extraction method adapt to satellite cloud image has to be used. Content-based satellite cloud image processing and information retrieval (CBIPIR) is a very important problem in image processing and analysis field. The basic character, like color, texture, edge and shape was extracted from the cloud image, and then the satellite cloud image database was provided to store the basic character information. Since traditional image retrieval method has some limitation, for realized image retrieval accurately and quickly, the CBIR method is adaptive. On the basis of the key technology of CBIPIR was studied, we could obtain the better retrieval effect, and the image retrieval result was shown in detail. The experiment result proves that the research and application of content-based satellite cloud image processing is valuable, which could improve the professional image application efficiency more.

Adaptive Extended Kalman Filtering for SINS/GPS Integrated Navigation Systems

An improved Adaptive Extended Kalman filtering algorithm is proposed here to estimate the measurement noise on-line for the SINS/GPS integrated navigation systems. The measurement remnant chi-square method is used to automatically adjust the sliding window basing on the innovation sequence. The experiment result shows that this new approach could improve the accuracy of the integrated navigation system effectively when the measurement noise is unknown.

Sigma-Point Kalman Filtering for tightly-coupled GPS/INS

This paper proposes the fusion of GPS measurements and inertial sensor data from gyroscopes and accelerometers in tightly-coupled GPS/INS navigation systems. Usually, an extended Kalman filter (EKF) is applied for this task. However, as system dynamic model as well as the pseudorange and pseudorange rate measurement models are nonlinear, the EKF is sub-optimal choice from theoretical point of view, as it approximates the propagation of mean an covariance of Gaussian random vectors through these nonlinear models by a linear transformation, which is accurate to first-order only. The sigma-point Kalman filter (SPKF) family of algorithms use a carefully selected set of sample points to more accurately map the probability distribution than linearization of the standard EKF, leading to faster convergence from inaccurate initial conditions in position and attitude estimation problems, which achieves an accurate approximation to at least second-order. Therefore, the performance of EKF and SPKF applied to tightly-coupled GPS/INS integration is compared in numerical simulations. It is found that the SPKF approach offers better performances over standard EKF.

SNN clustering kernel technique for content-based scene matching

In this paper, the radial basis vector (RBV) is proposed to describe the descriptor set of an image. And the shared nearest neighbor clustering kernel (SNNCK) technique is proposed to match RBV pairs. SNNCK is based on the charge attractive model, which will make the unequal-dimensional data sets clustering naturally. Thus, this novel algorithm is able to match the unequal-dimensional data sets when the number of descriptors of two images are unequal. It also can automatically extract the repetition pattern of the reference date set, which is helpful to avoid the wrong matching. Experimental results are also provided, and these results demonstrate superior performances of SNNCK algorithm by using the feature point sets with strong disturbs.

A New Method to Improve the Maneuver Capability of AUV Integrated Navigation Systems

The maneuver characteristic of the most commonly used AUV integrated navigation systems was investigated in this paper. After analyzing the error cause of conversional used Kalman filter of SINS/DVL integrated navigation systems in maneuver state, a novel method was proposed which is to use the output of complex navigation systems to revise the SINS in real-time, and an improved adaptive Kalman filter was discussed here to reach the seamless changing of the whole system. The measurement remnant method was introduced to judge whether the bearing change event happened or not. The whole design was aiming to reach the smooth transition between the different motion states and improve the maneuver capability of the AUV navigation system. The simulation results confirms the new approach could restrain the oscillation of Kalman filter in motion chang ing state and improve the accuracy of the AUV integrated navigation systems.