Self-alignment of full skewed RSINS：observability analysis and full-observable Kalman filter

Traditional orthogonal strapdown inertial navigation sys-tem （SINS） cannot achieve satisfactory self-alignment accuracy in the stationary base： taking more than 5 minutes and al the iner-tial sensors biases cannot get ful observability except the up-axis accelerometer. However, the ful skewed redundant SINS （RSINS） can not only enhance the reliability of the system, but also improve the accuracy of the system, such as the initial alignment. Firstly, the observability of the system state includes attitude errors and al the inertial sensors biases are analyzed with the global perspective method： any three gyroscopes and three accelerometers can be assembled into an independent subordinate SINS （sub-SINS）;the system state can be uniquely confirmed by the coupling connec-tions of al the sub-SINSs;the attitude errors and random constant biases of al the inertial sensors are observable. However, the ran-dom noises of the inertial sensors are not taken into account in the above analyzing process. Secondly, the ful-observable Kalman filter which can be applied to the actual RSINS containing random noises is established; the system state includes the position, ve-locity, attitude errors of al the sub-SINSs and the random constant biases of the redundant inertial sensors. At last, the initial self-alignment process of a typical four-redundancy ful skewed RSINS is simulated： the horizontal attitudes （pitch, rol ） errors and yaw error can be exactly evaluated within 80 s and 100 s respectively, while the random constant biases of gyroscopes and accelero-meters can be precisely evaluated within 120 s. For the ful skewed RSINS, the self-alignment accuracy is greatly improved, mean-while the self-alignment time is widely shortened.     

一种有效估计着陆引导信号多径时延的方法

利用导航信号收发已知且具有周期性的特点,提出了一种对着陆引导信号多径时延进行有效估计的方法。该方法首先计算相关函数,而后对相关函数进行二次微分,对时延值进行初步估计。最后通过直线拟合算法和比例拟合算法提高估计精度。通过计算机仿真,验证了算法的有效性。该算法具有在低采样率的条件下,估计精度高的特点。     

GPSNISNAV integrated relative navigation and attitude determination system for ultra-close spacecraft formation flying

For the improvement of accuracy and better fault-tolerant performance, a global position system (GPS)/vision navigation (VISNAV) integrated relative navigation and attitude determination approach is presented for ultra-close spacecraft formation flying. Onboard GPS and VISNAV system are adopted and a federal Kalman filter architecture is used for the total navigation system design. Simulation results indicate that the integrated system can provide a total improvement of relative navigation and attitude estimation performance in accuracy and fault-tolerance.     

两时间尺度的捷联速度算法研究

根据奇异摄动理论分析具有小参数的捷联惯导系统方程,在两时间尺度上对系统状态方程进行了降阶简化处理,设计捷联算法.在内回路推力速度矢量计算中,应用一种新的划船补偿算法补偿比力转换过程中载体姿态变化产生的速度误差.在外回路中进行重力地速计算,完成导航坐标系上速度的更新.仿真结果表明:新算法精度与Savage四子样算法近似,计算量小.     

基于遗传算法多目标非重叠路径诱导算法

依据遗传算法基本原理,提出一种多目标路径诱导算法. 染色体编码采用可变长度节点序列方法表示,以减少染色体编码长度. 设计了相应的多目标适应度函数. 该算法在给定多个目标约束条件下,能够解出多个近优路径. 实验结果证明,该算法能有效解决多目标非重叠路径选择问题,和目前已有其它方法相比,路径相似度更小.     

卫星导航定位系统(二十九)

介绍了中星-22号A通信卫星、一箭双星、鑫诺二号通信广播卫星、军用通信与导航卫星等的发射、升空和入轨之情况。     

基于车辆动力学的轨迹跟踪器设计

轨迹跟踪是移动机器人导航中的核心问题之一。针对非完整运动约束车辆,利用反馈线性化方法设计了轨迹跟踪器,仿真研究了跟踪算法的鲁棒性。最后,介绍了工程实现中参数观测器设计等相关问题。     

组合导航信息融合算法的研究

以GPS／INS组合导航系统为应用背景,推导了“当前统计”模型下卡尔曼滤波方程的关键矩阵。阐述了卡尔曼滤波器的主要参数对组合导航信息融合效果的影响;给出了组合导航系统的松耦合设计框图;根据实验测得的数据采用基于卡尔曼滤波的信息融合算法,通过对算法改进前后东向误差和北向误差的分析,说明算法改进后的定位精度比改进前高约30％．     

北斗一号卫星信号高灵敏度捕获方法

研究在复杂环境下弱北斗一号卫星信号的捕获方法.利用北斗一号卫星在同一频率上发射两个波束和帧头与卷尾组成已知连续信息序列的特点,可以对两个波束做长时间相干联合捕获.从增加捕获信号功率和减小非相干累加损失两个方面提高捕获灵敏度.仿真和实测结果表明,联合捕获方法可以捕获低于—133 dBm的信号,性能优于单波束串行搜索捕获方法.     

抗转发干扰FFT快速捕获方法研究

为了解决有效抑制转发式干扰问题,根据转发干扰信号的码相位滞后于卫星导航信号的特点,结合快速傅里叶变换(FFT)快速捕获的二维搜索策略,提出基于延迟-等待捕获策略的抗转发干扰FFT快速捕获方法.该方法根据过门限峰值的码相位信息来区分判别卫星导航信号和转发干扰信号,在不影响接收机在无转发干扰正常工作的条件下,保证了接收机在转发干扰下的捕获性能.理论分析和仿真实验验证了该方法的有效性.