In some tracking applications,due to the sensor characteristic,only range measurements are available.If this is the case,due to the lack of full position measurements,the observability of Cartesian states(e.g.,positio...In some tracking applications,due to the sensor characteristic,only range measurements are available.If this is the case,due to the lack of full position measurements,the observability of Cartesian states(e.g.,position and velocity)are limited to particular cases.For general cases,the range measurements can be utilized by developing a state estimation algorithm in range-Doppler(R-D)plane to obtain accurate range and Doppler estimates.In this paper,a state estimation method based on the proper dynamic model in the R-D plane is proposed.The unscented Kalman filter is employed to handle the strong nonlinearity in the dynamic model.Two filtering initialization methods are derived to extract the initial state estimate and the initial covariance in the R-D plane from the first several range measurements.One is derived based on the well-known two-point differencing method.The other incorporates the correct dynamic model information and uses the unscented transformation method to obtain the initial state estimates and covariance,resulting in a model-based method,which capitalizes the model information to yield better performance.Monte Carlo simulation results are provided to illustrate the effectiveness and superior performance of the proposed state estimation and filter initialization methods.展开更多
A Target State Estimator (TSE) for airborne radar system is proposed in this paper. It is very important for fire control system to obtain accurate estimation of the maneuvering target and the TSE becomes a key link i...A Target State Estimator (TSE) for airborne radar system is proposed in this paper. It is very important for fire control system to obtain accurate estimation of the maneuvering target and the TSE becomes a key link in the integrated Flight/Fire Control (IFFC) system. By adopting the Cartesian coordinates and pseudomeasurements ,the result ed TSE has it s advantages in computation.In addition, by employing accurate range and range-rate redundant filter, the range direction estimations obtained in Cartesian filter are greatly improved. The TSE shows its satisfaCtory performance in the Monte Carlo simulation of the IFFC system.展开更多
基金This work was supported by the National Natural Science Foundation of China(61671181,62101162).
文摘In some tracking applications,due to the sensor characteristic,only range measurements are available.If this is the case,due to the lack of full position measurements,the observability of Cartesian states(e.g.,position and velocity)are limited to particular cases.For general cases,the range measurements can be utilized by developing a state estimation algorithm in range-Doppler(R-D)plane to obtain accurate range and Doppler estimates.In this paper,a state estimation method based on the proper dynamic model in the R-D plane is proposed.The unscented Kalman filter is employed to handle the strong nonlinearity in the dynamic model.Two filtering initialization methods are derived to extract the initial state estimate and the initial covariance in the R-D plane from the first several range measurements.One is derived based on the well-known two-point differencing method.The other incorporates the correct dynamic model information and uses the unscented transformation method to obtain the initial state estimates and covariance,resulting in a model-based method,which capitalizes the model information to yield better performance.Monte Carlo simulation results are provided to illustrate the effectiveness and superior performance of the proposed state estimation and filter initialization methods.
文摘A Target State Estimator (TSE) for airborne radar system is proposed in this paper. It is very important for fire control system to obtain accurate estimation of the maneuvering target and the TSE becomes a key link in the integrated Flight/Fire Control (IFFC) system. By adopting the Cartesian coordinates and pseudomeasurements ,the result ed TSE has it s advantages in computation.In addition, by employing accurate range and range-rate redundant filter, the range direction estimations obtained in Cartesian filter are greatly improved. The TSE shows its satisfaCtory performance in the Monte Carlo simulation of the IFFC system.
