Subspace array processing for the suppression of FM jamming in GPS receivers

The mitigation of FM interference in GPS receivers is considered. In difference to commonly assumed wideband and narrowband interferers, the FM interferers are wideband, but instantaneously narrowband, and as such, have clear time-frequency (TF) signatures that are distinct from the GPS coarse acquisition (C/A) spread spectrum code. In the proposed technique, the estimate of the FM interference instantaneous frequency (IF) and the interference spatial signature are used to construct the spatiotemporal interference subspace. The IF estimates can be provided using existing effective linear or bilinear TF methods. The undesired signal arrival is suppressed by projecting the input data on the interference orthogonal subspace. With a multisensor receiver, the distinctions in both the spatial and TF signatures of signal arrivals allow effective interference suppressions. The deterministic nature of the signal model is considered and the known underlying structure of the GPS C/A code is utilized. We derive the receiver signal-to-interference-plus-noise ratio (SINR) under exact and perturbed IF values. The effect of IF estimation errors on both pseudorange measurements and navigation data recovery is analyzed. Simulation results comparing the receiver performances under IF errors in single and multiantenna GPS receivers are provided.     

Chaotic zero dynamics in kinematically redundant robots

The authors attempt to integrate two areas in robotics that are maturing rapidly: the control of kinematically redundant rigid robots and feedback linearization. Kinematically redundant robots have several advantages over nonredundant robot arms. The extra degrees of freedom are used to reach around or between obstacles. Unlike nonredundant rigid link robots that do not exhibit zero dynamics, the self motions of kinematically redundant robots can be used for torque optimization or avoiding obstacles. It is shown that induced self motions can be chaotic. The main contribution is to demonstrate chaos in cases of feedback linearization when the decoupling matrix is nonsquare and there are less outputs than inputs     

含连续／离散变量结构优化中的神经网络与变尺度模拟退火方法

传统的优化方法难于有效地处理含有连续／离散混合变量优化问题,本文介绍了一种改进的变尺度模拟退火方法并与人工神经网络能量函数模型相结合,用于求解含连续／离散设计变量的工程结构优化问题,较好地解决了模拟退火技术用于工程结构优化时选取具有全局性的初始点困难及迭代次数较多的弱点。算例表明,该方法可以使模拟退火算法从局部最优的陷阱中跳出,最后求出整体最优解。     

ExoMars Trace Gas Orbiter (TGO) Science Ground Segment (SGS)

The ExoMars Trace Gas Orbiter (TGO) Science Ground Segment (SGS), comprised of payload Instrument Team, ESA and Russian operational centres, is responsible for planning the science operations of the TGO mission and for the generation and archiving of the scientific data products to levels meeting the scientific aims and criteria specified by the ESA Project Scientist as advised by the Science Working Team (SWT). The ExoMars SGS builds extensively upon tools and experience acquired through earlier ESA planetary missions like Mars and Venus Express, and Rosetta, but also is breaking ground in various respects toward the science operations of future missions like BepiColombo or JUICE. A productive interaction with the Russian partners in the mission facilitates broad and effective collaboration. This paper describes the global organisation and operation of the SGS, with reference to its principal systems, interfaces and operational processes.