ID 原文 译文
38616 针对低轨星座协同探测弹道目标过程中存在系统误差的问题,提出多星载光学传感器系统误差极大似然配准(maximum likehood registration,MLR)算法。 For Leo constellation system error exists in the process of collaborative detection of ballistic target problem, put forward many space-borne optical sensors system error maximum likelihood registration (maximum likehood registration, MLR) provision algorithm.
38617 通过一阶Taylor近似对非线性量测转换线性化,推导出目标状态的误差协方差与卫星轨道定向、姿态角测量和传感器测量等随机误差的关系,并基于视线交叉获得观测在状态空间中的近似投影,从而将MLR算法扩展到低轨星座多光学传感器的误差配准。 Through a first order Taylor approximate linearization of the nonlinear measurement transformation, deduce the orientation of target state error covariance and satellite orbit and attitude Angle measurement and sensor measurement random error, and based on the line of sight cross observation approximation in the state space projection, thus extending the MLR algorithm to Leo constellation optical sensor error registration.
38618 通过引入各类测量误差的先验信息对目标状态的误差协方差进行修正,利用期望极大化迭代,实现了对系统误差的无偏有效估计及目标轨迹的融合估计。 By introducing all kinds of measurement error of prior information to modify the target state error covariance, using the expectation maximization iterative, implementation of the system error of the unbiased estimation and target track fusion estimation effectively.
38619 仿真验证了所提算法的有效性,且配准性能优越。 The simulation to verify the effectiveness of the proposed algorithm, and the registration of superior performance.
38620 海面舰船成像技术在军事和民用领域应用广泛。 The surface ship imaging technology has been widely applied in military and civil field.
38621 针对海面动目标成像定位模糊的缺点,提出了使用速度合成孔径雷达(velocity synthetic aperture radar,VSAR)估计动目标速度频率的方法。 On the surface of the moving target imaging positioning fuzzy shortcomings, puts forward the using rate of synthetic aperture radar (velocity synthetic aperture radar, VSAR) moving target speed frequency estimation method.
38622 首先,分析了VSAR的成像机理和限制条件,建立了基于相控阵雷达对海面舰船的成像模型; First of all, the paper analyzes the imaging mechanism of VSAR and limiting conditions, based on phased array radar imaging model of sea surface ships;
38623 然后,采用多天线图像域的速率频率估计方法纠正方位向的偏移,采用图像熵算法完成目标图像的自适应聚焦; Then, the rate of using multiple antenna image domain frequency estimation method to correct orientation to offset, to complete the target image using the algorithm of image entropy of self-focusing;
38624 最后,利用该方法对海面运动舰船进行仿真计算。 Finally, using the method of the surface ship simulation calculation.
38625 仿真结果表明,VSAR在处理大海域海面静动目标同时存在的场景下,可以甄别出目标所属类型,判断出动目标的运动趋势和航行轨迹。 VSAR simulation results indicate that the static and dynamic objectives in dealing with a big sea sea scenarios exist, can be identified by type, judge out the target movement trends and trajectory.