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中文摘要：
针对目标的运动模型和过程噪声的统计特性未知时难以进行目标跟踪和误差配准这一问题，提出了一种基于H∞滤波和当前统计模型的系统偏差估计方法。基于机动目标的当前统计模型，采用鲁棒H∞滤波算法对目标状态和系统偏差进行联合估计。本算法克服了对目标最大加速度的依赖，而且在目标过程噪声统计特性和运动模型未知的情况下，估计结果仍然很稳定。仿真结果表明，该算法不受目标运动模型的限制，能够有效地实现目标过程噪声统计特性未知情况下的误差配准。
英文摘要：
To improve the system errors estimation and target tracking performance under the condi- tion that the target motion model and statistical characteristics of process noise are unknown,a novel ro- bust estimation ter is used to e method of sensor bias based on H~ filter and current statistical model is proposed. H∞ fil- stimate target states and sensor bias simultaneously based on current statistical model. The disadvantage of the model depending on maximum acceleration is overcome and estimated results are still stable when target motion model and statistical characteristics of process noise are unknown. Simulation results show that the algorithm is not affected by the target motion model, and errors registration can be finished more effectively when statistical characteristics of process noise are unknown.
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