| Abstract: | The cooperative localization(CL)is affected by the communication topology among the platforms. Based on the unscented Kalman filtering,the distributed CL(DCL)oriented to the unpredicted communication topology is investigated. To improve the adaptability,the character of the look-up Cholesky decomposition is exploited for the covariance matrix decomposing. Then,the distributed U transformation can be dynamically implemented according to the available communication topology. In the proposed algorithm,the global information is not required for the individual,and only the available information from the neighbor is used. Each platform's state can be estimated independently. The error covariance of the state estimates can be updated in the single platform. The algorithm is adaptive to any serial communication topologies where the measuring to the measured platform is a starting path. The applicability of the proposed algorithm to unpredicted communication topology is improved,remaining equivalent localization performance to free connection communication. |
