Cubature Kalman filters: Derivation and extension

This paper focuses on the cubature Kalman filters （CKFs） for the nonlinear dynamic systems with additive process and measurement noise. As is well known, the heart of the CKF is the third-degree spherical–radial cubature rule which makes it possible to compute the integrals encountered in nonlinear filtering problems. However, the rule not only requires computing the integration over an n-dimensional spherical region, but also combines the spherical cubature rule with the radial rule, thereby making it difficult to construct higher-degree CKFs. Moreover, the cubature formula used to construct the CKF has some drawbacks in computation. To address these issues, we present a more general class of the CKFs, which completely abandons the spherical–radial cubature rule. It can be shown that the conventional CKF is a special case of the proposed algorithm. The paper also includes a fifth-degree extension of the CKF. Two target tracking problems are used to verify the proposed algorithm. The results of both experiments demonstrate that the higher-degree CKF outperforms the conventional nonlinear filters in terms of accuracy.

Parallel Construction Heuristic Combined with Constraint Propagation for the Car Sequencing Problem

For the car sequencing（CS） problem, the draw-backs of the ＂sliding windows＂ technique used in the objective function have not been rectified, and no high quality initial solution has been acquired to accelerate the improvement of the solution quality. Firstly, the objective function is improved to solve the double and bias counting of violations broadly discussed. Then, a new method combining heuristic with constraint propagation is proposed which constructs initial solutions under a parallel framework. Based on constraint propagation, three filtering rules are designed to intersecting with three greedy functions, so the variable domain is narrowed in the process of the construction. The parallel framework is served to show its robustness in terms of the quality of the solution since it greatly increases the performance of obtaining the best solution. In the computational experiments, 109 instances of 3 sets from the CSPLib＇ s benchmarks are used to test the performance of the proposed method. Experiment results show that the proposed method outperforms others in acquiring the best-known results for 85 best-known results of 109 are obtained with only one construction. The proposed research provides an avenue to remedy the deficiencies of ＂sliding windows＂ technique and construct high quality initial solutions.