Based on the analysis of vehicle navigation status and vehicle static navigation shortage,and data fusion technology of real-time GPS data and overhead road loop coil detector data,the architecture of real-time traffic information service system of dynamic oriented navigation is presented,which realizes the urban road traffic state estimate.
In actual target tracking system of the sensors data fusion,for the bad influences of the measurement values including outliers to state estimate,the algorithm calculates the fuzzy clingy degree of measurement value of arbitrary two sensors on space based on the theories of probability source combination and characteristic vector of non-negative matrix,at the same time the synthetic fuzzy clingy degree of each sensor measurement value and other sensors measurement values is fused in time,and the weight of each sensor.
The simulation results indicates that this method can not only solve the combination explosion problem of calculation caused by traditional method, but also get more accuracy and creditability in maneuver target status estimation.
The angle of infrared with high accuracy is fused with the range of radar with high accuracy. As a result the discrimination between the fusion track and the real track becomes smaller and the status estimation of the target gets more accurate.
Bayes fusion estimation of dynamic parameters is given by using hierarchical Bayes estimation method and discrete linear model status estimation method in a hierarchical model of multidimensional dynamic parameters.
In addition, this paper presents a couple of programs compiled in FORTRAN 77. As a patch to the dispatcher power flow application, these programs shield the undesirable PV node and PV voltage data acquired from status estimate application.
The similitude degree and similitude degree matrix are defined by using the normal difference of status estimate vectors (or measures). The consistency measure is given using spacial information and the reliability measure is given using temporal information. Then the sensor combination and fusion weights are proposed and the space-time fusion is made.
The three indicators of estimated error, residual tolerance and objective function are collected statistics through ex-perimental method, paying much attention to parameter error in status estimation, and the effect of parameter error on the status estimate is analyzed comprehensively.
Finally, the ultimate state estimation of each target is calculated according to the new model probability, and the state estimation is transmitted to each sensor.
This paper has taken on a new perspective and modeled the problem as a state estimation problem with finite communication constraints.
The stochastic 2-D FMM II with multiplicative noise can be reduced to a 1-D model, and the proposed optimal filtering algorithm for the stochastic 2-D FMM II with multiplicative noise is obtained by using the state estimation theory of 1-D systems.
Next, an optimal state feed back controller using the Kalman filter state estimation technique is derived.
Directional interference suppression is based on a recursive state estimation of Kalman filter.
Presented were the basic methods of constructing the asymptotic observers for the nonlinear dynamic systems with control and the approaches to system stabilization using the system state estimate made by the observer.
The exponential observers (extended Kalman or Luenberger observers, high gain observers) allow the use of a tuning parameter for managing the rate of convergence of the state estimate towards the true state.
The challenging terrain over which the rover will necessarily traverse tends to seriously degrade a dead-reckoned state estimate, given severe wheel slip and/or interaction with obstacles.
Second, the rover is able to match successively constructed terrain maps to obtain a vision-based state estimate which can then be fused with wheel odometry to obtain a much improved state estimate.
Finally the rover makes use of this state estimate to perform autonomous real-time path planning and navigation to user designated goals.