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中文摘要：
针对工程上难以对3D雷达与2D雷达进行直接配准这一问题，提出了一种基于H∞滤波和当前统计模型的目标状态和系统偏差联合估计方法。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，该算法要优于基于实时卡尔曼滤波的3D雷达和2D雷达配准算法，并且不受目标运动模型的限制。
英文摘要：
Aimed at the difficulty to register 3D radar and 2D radar directly in engineering applica- tion, a novel estimation method of target states and sensor bias based on H∞ filter and current statistical model （CSHF） is proposed. H∞ filter is used to estimate 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 under the condition that the target motion model and statistical characteristics of process noise are unknown. Simulation results show that the algorithm outperforms bias alignment method of 3D radar and 2D radar based on Real-time Kalman Filter （RTKF）,but also it is not affected by the target motion model.
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