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351.
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The Active Rack Isolation System [ARIS] International Space Station [ISS] Characterization Experiment, or ARIS-ICE for short, is a long duration microgravity characterization experiment aboard the ISS. The objective of the experiment is to fully characterize active microgravity performance of the first ARIS rack deployed on the ISS. Efficient ground and on-orbit command and data handling [C&DH] segments are the crux in achieving the challenging objectives of the mission. The objective of the paper is to provide an overview of the C&DH architectures developed for ARIS-ICE, with the view that these architectures may serve as a model for future ISS microgravity payloads. Both ground and on-orbit segments, and their interaction with corresponding ISS C&DH systems are presented. The heart of the on-orbit segment is the ARIS-ICE Payload On-orbit Processor, ARIS-ICE POP for short. The POP manages communication with the ISS C&DH system and other ISS subsystems and payloads, enables automation of test/data collection sequences, and provides a wide range of utilities such as efficient file downlinks/uplinks, data post-processing, data compression and data storage. The hardware and software architecture of the POP is presented and it is shown that the built-in functionality helps to dramatically streamline the efficiency of on-orbit operations. The ground segment has at its heart special ARIS-ICE Ground Support Equipment [GSE] software developed for the experiment. The software enables efficient command and file uplinks, and reconstruction and display of science telemetry packets. The GSE software architecture is discussed along with its interactions with ISS ground C&DH elements. A test sequence example is used to demonstrate the interplay between the ground and on-orbit segments.  相似文献   
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  总被引:2,自引:0,他引:2  
An on-board mosaic sensor is staring down from a satellite to afixed point on the ground while collecting frames that contain targetsignatures and background noise. A dynamic programmingalgorithm (DPA) has been developed to optimally detect dim movingtargets that cross the sensor's field of view. The algorithm has beendescribed in Part I of this paper. Here, in Part II, we analyze thealgorithm performance and compare it with that of a simpleassembling of thresholded frames; the DPA's SNR performance isshown to be at least an order of magnitude better.  相似文献   
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Classical bearings-only target-motion analysis (TMA) is restricted to sources with constant motion parameters (usually position and velocity). However, most interesting sources have maneuvering abilities, thus degrading the performance of classical TMA. In the passive sonar context a long-time source-observer encounter is realistic, so the source maneuver possibilities may be important in regard to the source and array baseline. This advocates for the consideration and modeling of the whole source trajectory including source maneuver uncertainty. With that aim, a convenient framework is the hidden Markov model (HMM). A basic idea consists of a two-levels discretization of the state-space. The probabilities of position transition are deduced from the probabilities of velocity transitions which, themselves, are directly related to the source maneuvering capability. The source state sequence estimation is achieved by means of classical dynamic programming (DP). This approach does not require any prior information relative to the source maneuvers. However, the probabilistic nature of the source trajectory confers a major role to the optimization of the observer maneuvers. This problem is then solved by using the general framework of the Markov decision process (MDP)  相似文献   
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The performance analysis of source trajectory estimation using measurements provided by multiple platforms (or arrays) is studied. In numerous practical situations, the maneuvering ability of the receiver (e.g., a ship towing linear arrays) is limited, leading to the assumption that the observer motion is rectilinear and uniform. Even if this hypothesis appears quite restrictive, practical and tactical considerations fully justify its interest. This leads to consider multiple (platform) target motion analysis (denoted MTMA) and to analyze the performance of such trajectory estimation methods  相似文献   
359.
  总被引:3,自引:0,他引:3  
This paper analyzes the state of the ionosphere during two geomagnetic storms of a different intensity evolving in different sectors of local time in different seasons. There were used the data from a network of ionospheric stations located in the opposite longitudinal sectors of 80°-150° E and 250°-310° E.This analysis has permitted us to conclude that the detected differences in the variations of the disturbances are likely to be determined by the local time difference of the geomagnetic storm development, its intensity and by the different illumination conditions of the ionosphere.  相似文献   
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The problem of target motion analysis (TMA) has been the subject of an important literature. However, present methods use data estimated by a short time analysis (azimuths, Dopplers, etc.). For far sources, the nonstationarities of the array processing outputs, induced by the sources motion, may be simply modeled. This model leads one to consider directly a spatio-temporal TMA. Then new (spatio-temporal) data can be estimated. These estimates correspond to a long time analysis. Further, note that they are estimated independently of the (classical) bearings. In this general framework, the concept of source trajectory replaces the classical instantaneous bearings. Corresponding TMA algorithms are then studied. Then the study of statistical performance is carefully studied  相似文献   
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