基于单天线GPS的伪姿态测量算法研究

介绍了根据单天线GPS速度测量值测定载体伪姿态的基本算法原理,建立了卡尔曼滤波方程,改进了伪航向角的计算和卡尔曼滤波模型,并进行了算法仿真。结果表明,在载体进行中高速飞行时,单天线测姿算法具有较高的精度,基本满足常规姿态测量要求。     

无人机下滑着陆DGPS/INS导航及引导系统的仿真与试验研究

介绍了一种采用输出校正方式DGPS/INS组合导航系统引导无人机下滑着陆的方案。给出了该方案的数学模型,对组合导航系统进行了数字仿真,并在数字仿真的基础上进行了动态跑车试验,验证了所设计的输出校正方式DGPS/INS组合导航系统能够满足引导无人机自动下滑着陆的精度要求。     

一种快速求解整周模糊度的方法

针对FARA方法搜索整周模糊度组合数比较大,LAMBDA方法需要浮点解精度比较高的缺点,提出一种求解GPS载波相位测量整周模糊度的分步法。用LAMBDA方法搜索出来的整周模糊度作为FARA方法的初始解,进而用FARA方法解算出它的最终解。实验结果表明,该方法能缩短搜索整周模糊度的时间,快速准确地确定整周模糊度。     

欺骗干扰条件下的GPS定位方程求解性能研究

介绍了GPS定位欺骗原理,并对GPS 转发式欺骗干扰原理和定位方程求解的算法进行了分析阐述.采用仿真的手段,重点分析了多种典型欺骗条件下的接收机定位解算结果,特别是对四站定位时干扰的效果进行了详细仿真解算和讨论,给出了有意义的结论,可为欺骗干扰的效果评估及战术应用提供有益参考.     

GPS空间分集接收机

为解决传统单天线GPS接收机在载体旋转情况下不能连续跟踪卫星连续定位和速度偏差较大的问题,提出一种GPS空间分集接收机设计方案。该接收机采用空间分集算法和消旋解算方法,能稳定连续地跟踪GPS卫星信号,并准确地求解出载体的平动速度。     

真航向测量系统初始对准中的UKF应用研究

研究了“真航向测量系统”（简称TNDS True North Determination System) , TNDS组合中等精度的INS和MS860型GPS系统,应用UKF (Unscented Kalman Filter）最优估计滤波算法,实现的高精度快速初始对准。论文重点推导了TNDS初始对准的非线性误差模型,并实现了TNDS中基于该模型的UKF滤波,TNDS系统的UKF组合初始对准算法最后进行系统试验测试。试验数据表明：采用了UKF滤波后,TNDS的航向初始对准中,航向失准角为25. 时,达到同样的对准精度0.1. , INS自对准时间由原来的2879s缩短为179s;纵横摇的失准角对准到同样的精度内,时间相应的减小了一个量级;同时TNDS速度的发散也得到了抑制。
      

INTEGRATED GPS/INS OF PSEUDO-RANGE DELTA-RANGE SEMI-PHYSICAL SIMULATION'S RESEARCH

In order to further study the performance of tightly integrated navigation system of GPS/INS, a semi-physical simulation of tightly coupled system has been done based on the data gathered from the experiment of integrated system of GPS and INS. The closed-loop Kalman Filter and U-D discompose algorithm have been used. The simulation results associated to four integrated models of pseudo-range, delta-range, pseudo-range and delta-range alternation, and pseudo-range and delta-range synthesis have been provided, and the actual effects of variously integrated models have been analyzed. The results show that the pseudo-range and delta-range synthesis coupled model is the most effective to improve the coupled system performance and the individual delta-range coupled model had better be avoided in application.     

Aiming at a 1-cm Orbit for Low Earth Orbiters: Reduced-Dynamic and Kinematic Precise Orbit Determination

The computation of high-accuracy orbits is a prerequisite for the success of Low Earth Orbiter (LEO) missions such as CHAMP, GRACE and GOCE. The mission objectives of these satellites cannot be reached without computing orbits with an accuracy at the few cm level. Such a level of accuracy might be achieved with the techniques of reduced-dynamic and kinematic precise orbit determination (POD) assuming continuous Satellite-to-Satellite Tracking (SST) by the Global Positioning System (GPS). Both techniques have reached a high level of maturity and have been successfully applied to missions in the past, for example to TOPEX/POSEIDON (T/P), leading to (sub-)decimeter orbit accuracy. New LEO gravity missions are (to be) equipped with advanced GPS receivers promising to provide very high quality SST observations thereby opening the possibility for computing cm-level accuracy orbits. The computation of orbits at this accuracy level does not only require high-quality GPS receivers, but also advanced and demanding observation preprocessing and correction algorithms. Moreover, sophisticated parameter estimation schemes need to be adapted and extended to allow the computation of such orbits. Finally, reliable methods need to be employed for assessing the orbit quality and providing feedback to the different processing steps in the orbit computation process. This revised version was published online in August 2006 with corrections to the Cover Date.     

H_∞滤波算法及其在GPS/SINS组合导航系统中的应用

 在对 H∞ 估计问题进行数学描述的基础上,建立了一种 H∞ 次优滤波算法的迭代方程。定性讨论了H∞滤波算法与传统 Kalman滤波器的关系,通过在 GPS/SINS组合系统中的实际应用进一步从精度、鲁棒性等性能指标方面对 H∞ 滤波和 Kalman滤波算法进行了比较。仿真结果表明,在理想条件下,Kalman滤波方法具有较高的精度;但是,当系统模型和外部干扰统计特性发生变化时,H∞ 滤波算法明显具有良好的鲁棒性能,同时,估计精度也较高,有效地克服了 Kalman滤波器存在的局限性。