无源跟踪观测信息的融合优化滤波算法研究

为充分利用探测设备可测得的到达时间、到达方向和多普勒频率等空域、时域与频域信息,提出了一种新的单站无源定位系统数据融合优化滤波算法。给出了算法的基本原理及其模型。仿真结果表明：与传统算法相比,该算法具更好的定位精度和收敛速度,是一种有效、可行的定位算法。     

基于LMS算法的自适应数字预失真技术研究

文章研究了基于查找表LUT方法的功率放大器自适应数字预失真技术。针对传统的基于线性收敛算法的自适应收敛速度较慢的不足,文章根据自适应滤波理论中的LMS算法,推导并仿真验证了适用于功率放大器自适应数字预失真技术的LMS算法,并从功率放大器的传输特性、输出频谱等方面将此算法与线性收敛的Rascal算法进行比较,仿真结果表明了LMS算法收敛速度更快、预失真效果更好。     

高速16QAM数据传输技术研究

文章简要介绍16QAM技术及其性能特点,介绍国外16QAM技术的应用情况和最新技术,重点对TWTA非线性对16QAM传输影响进行仿真和分析;针对16QAM传输体制,提出减小非线性影响的方案,同时对16QAM需求和应用前景进行了分析。     

基于扩展Kalm an滤波的实时测速定轨算法

针对实时测速定轨 (即只用测速数据确定运动目标的状态参数 )的实现问题 ,研究了一种扩展 Kalman滤波方法 ,并利用其状态方程和线性化观测方程得到定轨算法。理论推导和仿真结果表明 ,此算法是收敛的 ,且精度较高。     

国防原子时测试系统的设计与实现

随着现代武器系统的日趋高速化、自动化和智能化,时间频率在高技术战争中的地位越来越突出,国防原子时系统的运行研究,将对我国独立自主的时间标准系统的建立提供有利的技术支持。本文较详尽地阐述了国防原子时测试系统的组成,并介绍了系统中比对测试软件、环境监测系统的设计以及相关数据库的搭建。     

一种靶场试验遥测数据处理与分析系统的设计与实现

针对靶场试验遥测数据特点,设计了一种遥测数据处理分析系统。作为靶场测试流程和飞行结果判别的重要环节,遥测数据处理分析系统软件实现了繁杂测试数据处理与发布、数据管理和数据判读与服务等功能。该系统的设计与实现为靶场数字化建设提供了重要支撑,具有较强的实用性与推广价值。     

The impact of error covariance matrix structure of GRACE’s gravity solution on the mass flux estimates of Greenland ice sheet

The error variance-covariance matrices of the monthly GRACE gravity field models are usually well-structured (e.g., order-leading) to contain the error information of the monthly gravity field models, and they are important information to further improve the accuracy of the estimated mass transportation by a post-processing scheme. Intensive studies have been performed to understand the impact of different approximations of the full error variance-covariance matrix on the mass estimates obtained with the conventional GRACE-post processing methods (e.g., the de-striping method). In this study, based on the variants of the mascon approach which treat monthly GRACE solutions as input, we consider four different structures to the error variance-covariance matrix, (i) full matrix, (ii) block diagonal matrix, (iii) diagonal matrix, and (iv) identity matrix, and examine their impact on the mass transport estimates in Greenland. Using both synthetic and real data, we analyze the results at four temporal scales: (i) the long-term decadal scale, (ii) the inter-annual scale, (iii) the seasonal scale, and (iv) the monthly scale. Based on the synthetic study, we find that for the recovery of the long-term trend, the application of the diagonal structure obtains the best estimates. This is caused by the amplification of the model error in the mascon approach when considering the full and block diagonal structures of error variance-covariance matrix, not due to any imperfection of them. Therefore, we emphasize that one should be aware of mascon model deficiency in the mascon approach. Furthermore, the best inter-annual, seasonal and monthly mass estimates are derived by considering the block diagonal and full structures. This is caused by the behavior of the bias and the unique parameterization error in the case of different structures. A similar finding is also presented in the real data case. Finally, our analysis denotes the necessity of releasing the block diagonal structure together with the official monthly gravity field model for the GRACE Follow-On mission, instead of releasing only the diagonal structure as done for the GRACE mission.     

A novel method for destriping of OCM-2 data and radiometric performance analysis for improved ocean color data products

Despite the capability of Ocean Color Monitor aboard Oceansat-2 satellite to provide frequent, high-spatial resolution, visible and near-infrared images for scientific research on coastal zones and climate data records over the global ocean, the generation of science quality ocean color products from OCM-2 data has been hampered by serious vertical striping artifacts and poor calibration of detectors. These along-track stripes are the results of variations in the relative response of the individual detectors of the OCM-2 CCD array. The random unsystematic stripes and bandings on the scene edges affect both visual interpretation and radiometric integrity of remotely sensed data, contribute to confusion in the aerosol correction process, and multiply and propagate into higher level ocean color products generated by atmospheric correction and bio-optical algorithms. Despite a number of destriping algorithms reported in the literature, complete removal of stripes without residual effects and signal distortion in both low- and high-level products is still challenging. Here, a new operational algorithm has been developed that employs an inverted gaussian function to estimate error fraction parameters, which are uncorrelated and vary in spatial, spectral and temporal domains. The algorithm is tested on a large number of OCM-2 scenes from Arabian Sea and Bay of Bengal waters contaminated with severe stripes. The destriping effectiveness of this approach is then evaluated by means of various qualitative and quantitative analyses, and by comparison with the results of the previously reported method. Clearly, the present method is more effective in terms of removing the stripe noise while preserving the radiometric integrity of the destriped OCM-2 data. Furthermore, a preliminary time-dependent calibration of the OCM-2 sensor is performed with several match-up in-situ data to evaluate its radiometric performance for ocean color applications. OCM-2 derived water-leaving radiance products obtained after calibration show a good consistency with in-situ and MODIS-Aqua observations, with errors less than the validated uncertainties of ±5% and ±35% endorsed for the remote-sensing measurements of water-leaving radiance and retrieval of chlorophyll concentrations respectively. The calibration results show a declining trend in detector sensitivity of the OCM-2 sensor, with a maximum effect in the shortwave spectrum, which provides evidence of sensor degradation and its profound effect on the striping artifacts in the OCM-2 data products.     

CCPT系统中基于副边阻抗调制技术的反向信号与能量叠加传输技术研究

为了解决金属环境条件下的无线供电和信号传输需求，提出了一种基于电容耦合方式的无线能量和信号并行传输方案。通过建立E类放大器的数学模型，分析电容耦合系统的传输特性和阻抗影响机理，设计了适用于E类放大器结构的调制与解调电路，并通过仿真验证了电路的可行性，为CCPT系统从能量传输到信号回传提供了系统性的理论指导。     

A new method for improving the performance of an ionospheric model developed by multi-instrument measurements based on artificial neural network

There are remarkable ionospheric discrepancies between space-borne (COSMIC) measurements and ground-based (ionosonde) observations, the discrepancies could decrease the accuracies of the ionospheric model developed by multi-source data seriously. To reduce the discrepancies between two observational systems, the peak frequency (foF2) and peak height (hmF2) derived from the COSMIC and ionosonde data are used to develop the ionospheric models by an artificial neural network (ANN) method, respectively. The averaged root-mean-square errors (RMSEs) of COSPF (COSMIC peak frequency model), COSPH (COSMIC peak height model), IONOPF (Ionosonde peak frequency model) and IONOPH (Ionosonde peak height model) are 0.58 MHz, 19.59 km, 0.92 MHz and 23.40 km, respectively. The results indicate that the discrepancies between these models are dependent on universal time, geographic latitude and seasons. The peak frequencies measured by COSMIC are generally larger than ionosonde’s observations in the nighttime or middle-latitudes with the amplitude of lower than 25%, while the averaged peak height derived from COSMIC is smaller than ionosonde’s data in the polar regions. The differences between ANN-based maps and references show that the discrepancies between two ionospheric detecting techniques are proportional to the intensity of solar radiation. Besides, a new method based on the ANN technique is proposed to reduce the discrepancies for improving ionospheric models developed by multiple measurements, the results indicate that the RMSEs of ANN models optimized by the method are 14–25% lower than the models without the application of the method. Furthermore, the ionospheric model built by the multiple measurements with the application of the method is more powerful in capturing the ionospheric dynamic physics features, such as equatorial ionization, Weddell Sea, mid-latitude summer nighttime and winter anomalies. In conclusion, the new method is significant in improving the accuracy and physical characteristics of an ionospheric model based on multi-source observations.