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误差源分析是一个系统产品精度保障的前提条件.介绍了InSAR高程测量的基本原理;根据基本原理,从影响高程测量精度的基线长度、基线倾角、相位差、雷达天线到地面目标点的距离以及雷达天线高度等5个要素着手;依据这5个要素的产生过程,结合基于编队卫星InSAR系统的特点对系统的误差源进行了研究;最后较系统地分析出了影响编队卫星InSAR系统的误差源. 相似文献
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一种机载双天线InSAR干涉参数定标新方法 总被引:3,自引:2,他引:1
干涉参数定标对于机载双天线InSAR系统的大面积高精度数字高程模型获取具有重要意义。为了高效地进行干涉参数定标,从双天线InSAR获取DEM的基本原理出发,构建一种考虑干涉相位偏置、基线长度和基线水平角三个参数的定标新模型,设计该定标模型的未知参数解算方案。利用GPS实测的高程控制点对中国科学院电子学研究所自主研制的机载双天线InSAR系统进行了干涉参数定标实验,统计利用定标后干涉参数反演地面高程的误差,验证该干涉参数定标模型及解算方案。 相似文献
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结合SAR成像原理,在提出了基于DGPS/IMU数据的机载InSAR系统DEM三维坐标求解的基础上,推导出了基线长度、基线倾角、相位差、雷达天线到地面目标点的距离、雷达天线位置、中心多普勒频率及飞机飞行速度等因素误差对DEM精度的影响公式,分析讨论了机载InSAR系统影响精度的主要因素及系统可实现的性能情况,提出了机载InSAR系统部分设计建议,并使用实际的机载InSAR数据进行了试验。结果表明,本方法结果与实际试验统计的精度基本一致,影响精度的分析结论正确。 相似文献
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星载差分合成孔径雷达干涉测量(differential interferometric synthetic aperture radar,DInSAR)技术已经广泛应用于大范围的地表形变监测,但星载合成孔径雷达(synthetic aperture radar,SAR)数据获取的地表形变易受大气噪声的影响,且长时间的重访周期会导致像对之间的失相干。为了有效减弱这些影响,提出了利用零空间基线的车载合成孔径雷达干涉测量(interferometric synthetic aperture radar,InSAR)系统监测公路边坡形变的方法。在车载双天线系统采集不同时相的公路边坡SAR数据时,通过轨道控制使得异时相干涉对的空间基线接近零,从而使得利用DInSAR数据进行形变信息提取时可以减少去平地相位的过程,极大地简化了差分干涉处理的流程。以中国湖北省武汉市某区域获取的车载双天线InSAR数据为例,使用所提出的方法对7个布设的角反射器点进行形变精度分析,得到形变值均方根误差为2.206 mm。 相似文献
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基于卫星鳊队InSAR系统的卫星编队特点,阐述了在卫星飞行方向(方位向)产生基线的原因,提出了由方位向基线所引起的干涉相位改正方法,分析了一般情况下卫星鳊队InSAR系统的相位改正情况和对InSAR高程测量精度的影响。 相似文献
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InSAR系列讲座5:InSAR系统中的误差传播 总被引:3,自引:0,他引:3
作为InSAR系列讲座的第五篇,本文介绍InSAR高程与形变测量中的误差来源,对主要误差源(干涉相位、基线参数和地形数据)推导出误差传播模型。此外,还将讨论地形数据误差对干涉形变测量的影响。 相似文献
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为降低系统模型误差及观测模型误差的影响,结合噪声协方差自适应控制机制,对双天线GNSS/INS初始对准方法进行改进。利用噪声协方差自适应控制下的扩展卡尔曼滤波进行数据处理,包括系统噪声协方差控制及观测噪声协方差控制。试验结果表明,系统噪声协方差自适应控制机制可提高系统稳定性,降低滤波稳态值;观测噪声协方差自适应控制机制可降低观测噪声的影响,提高对准绝对精度。采用后处理的方式,利用基线长度偏差最小的基线结果辅助姿态解算,绝对精度进一步提高,对准绝对精度主要受观测值影响。利用本文方法,横滚角、俯仰角对准绝对精度可达0.02°,航向角对准绝对精度可达0.04°。 相似文献
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多路径误差为一时空环境效应,难以构建准确数学模型消除其影响,且该误差在基线两端不具有空间相关性,运用现有差分技术也无法很好消除,是高精度短基线测量中主要误差之一.为进一步削弱多路径误差,本文以监测站坐标时间序列中多路径误差为研究对象,根据多路径误差在历元间的时变特性,建立多路径误差状态空间模型,采用标准卡尔曼滤波和顾及有色噪声的卡尔曼滤波从监测站第一天双差固定解坐标残差序列中估计多路径误差改正序列,并根据多路径误差的周日重复特性,利用第一天得到的多路径误差改正序列对之后各天坐标序列进行改正.最后通过实验分析,得出顾及有色噪声的卡尔曼滤波估计方法优于标准卡尔曼滤波的结论.研究方法对提高GNSS定位精度具有重要实用价值. 相似文献
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面向宽基线立体影像匹配的高质量仿射不变特征提取方法 总被引:5,自引:1,他引:4
针对宽基线影像匹配问题,提出基于信息量和空间分布均衡性双重约束的多层次特征筛选方法,并在此基础上探讨集成该特征筛选方法、MSER(Maximally Stable Extremal Region detector)、SIFT(Scale Invariant Scale Transformation)的特征提取算法,以达到提取高质量(高信息量、空间分布均衡、高重复率)仿射不变特征的目的。实验表明,相对现有最优算法,本文方法具有更高的重复率和匹配成功率,更有利于后续的(宽基线)立体匹配。 相似文献
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Real-time seismic signal enhancement utilizing a hybrid Rao-Blackwellized particle filter and hidden Markov model filter 总被引:3,自引:0,他引:3
This letter outlines a novel and robust algorithm for identifying seismic events within low signal-to-noise ratio (SNR) passive seismic data in real time. Since the event detection problem is a continuous, real-time process which has nonlinear mathematical representations, a Rao-Blackwellized particle filter (RBPF) is utilized. In this algorithm, a jump Markov linear Gaussian system (JMLGS) is defined where changes (i.e., jumps) in the state-space system and measurement equations are due to the occurrences and losses of events within the measurement noise. The RBPF obtains optimal estimates of the possible seismic events by individually weighting and subsequently summing a bank of Kalman filters (KFs). These KFs are specified and updated by samples drawn from a Markov chain distribution which defines the probability of the individual dynamical systems which compose the JMLGS. In addition, a hidden Markov model filter is utilized within the RBPF filter formulation so that real-time estimates of the phase of the seismic event can be obtained. The filter is demonstrated to provide up to an 80-fold improvement in the SNR when processing simulated seismic data with Gauss-Markov measurement noise. 相似文献
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针对月球车定位,设计和推导了一种基于甚长基线干涉测量(very long baseline interferometry,VLBI)和天文导航系统(celestial navigation system,CNS)相结合的月球车联合定位方法,并采用联邦卡尔曼滤波来实现位置信息的最优估计以增强系统的可靠性和容错能力。最后,通过嫦娥-3号(CE-3)实测数据的解算证明了该方法较使用最小二乘法进行联合解算和单独采用VLBI方法定位,可以获得更高的月球车定位精度。同时,也有效地保障了月球车定位的可靠性和稳定性。 相似文献
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利用精密单点定位(Precise Point Positioning,PPP)获得的时间传递结果受到非模型化误差和观测噪声的影响,这些误差和噪声表现出随机噪声特性,因此,对时间传递数据进行平滑是一项非常重要的任务.将天文数据处理中广泛应用的Vondrak平滑方法应用于PPP时间传递的消噪中,采用观测误差法选取较为合理的平滑因子,并对实测数据进行平滑处理,结果表明:Vondrak平滑法可有效地滤除PPP数据的随机噪声,不仅可以提高时间传递的精确度,也能明显改善PPP时间传递所体现的频率稳定度. 相似文献
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Multipath on carrier phase measurements is among the major error sources for short baseline positioning. A new method is proposed
to improve the accuracy of the positioning results by mitigating the multipath effects on carrier phase measurements using
the variable length Least Mean Square (VLLMS) adaptive filter. The performance of the filter is analyzed as well as compared
with that of the standard LMS adaptive filter using a set of carrier phase observation data of two consecutive days collected
in a short baseline experiment. Because the two antennas are static, the multipath error is the only dominant component in
the carrier phase double-differenced residuals and indicates a repeated pattern. The numerical results show that both filters
can significantly mitigate the multipath effects in carrier phase double-differenced residuals, and hence improve the positioning
results. Furthermore, the VLLMS filter that reduces up to about 47.4% of the multipath effects on 3D positioning performs
better than the LMS filter that only reduces 22.0%. Both filters are suitable for real-time applications. 相似文献
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如何提高利用GPS获取车载系统航向角的精度是当前研究的热点之一。本文介绍了一种利用固定基线长的双GPS天线求车载航向角的新方法,该方法针对GPS的误差特点并结合"当前"统计模型,建立了适合航向角滤波的系统方程,然后利用卡尔曼滤波来消除航向角噪声,并且将基线长约束引入模型建立虚拟观测值进行处理。结果表明,该方法显著地提高了的航向角精度。 相似文献
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Differential carrier phase observations from GPS (Global Positioning System) integrated with high-rate sensor measurements,
such as those from an inertial navigation system (INS) or an inertial measurement unit (IMU), in a tightly coupled approach
can guarantee continuous and precise geo-location information by bridging short outages in GPS and providing a solution even
when less than four satellites are visible. However, to be efficient, the integration requires precise knowledge of the lever
arm, i.e. the position vector of the GPS antenna relative to the IMU. A previously determined lever arm by direct measurement
is not always available in real applications; therefore, an efficient automatic estimation method can be very useful. We propose
a new hybrid derivative-free extended Kalman filter for the estimation of the unknown lever arm in tightly coupled GPS/INS
integration. The new approach takes advantage of both the linear time propagation of the Kalman filter and the nonlinear measurement
propagation of the derivative-free extended Kalman filter. Compared to the unscented Kalman filter, which in recent years
is typically used as a superior alternative to the extended Kalman filter for nonlinear estimation, the virtue of the new
Kalman filter is equal estimation accuracy at a significantly reduced computational burden. The performance of the new lever
arm estimation method is assessed with simulated and real data. Simulations show that the proposed technique can estimate
the unknown lever arm correctly provided that maneuvers with attitude changes are performed during initialization. Field test
results confirm the effectiveness of the new method. 相似文献