Comparison of the transport codes HZETRN,HETC and FLUKA for galactic cosmic rays

The HZETRN deterministic radiation code is one of several tools developed to analyze the effects of harmful galactic cosmic rays (GCR) and solar particle events on mission planning and shielding for astronauts and instrumentation. This paper is a comparison study involving the two Monte Carlo transport codes, HETC–HEDS and FLUKA and the deterministic transport code, HZETRN. Each code is used to transport an ion from the 1977 solar minimum GCR spectrum impinging upon a 20 g/cm² aluminum slab followed by a 30 g/cm² water slab. This research is part of a systematic effort of verification and validation to quantify the accuracy of HZETRN and determine areas where it can be improved. Comparisons of dose and dose equivalent values at various depths in the water slab are presented in this report. This is followed by a comparison of the proton and forward, backward and total neutron flux at various depths in the water slab. Comparisons of the secondary light ion ²H, ³H, ³He and ⁴He fluxes are also examined.     

一种新的DBL-CDMA扩频码

构造了特殊的复数扩展矩阵,将基本松同步码(LS,Loose Synchronous)和复数扩展矩阵进行克罗内克积,设计出一种道本实验室码分多址(DBL-CDMA,Dan Ben Lab Code Division Multiple Access)互补分组地址码.分析了该地址码的自相关和互相关特性,以及该地址码的实现方法.分析结果表明,相对于基本LS码,在和基本LS码码长一致下,DBL-CDMA互补地址码增加了零相关窗口宽度、可用的码字数量和理想互补码的个数.该地址组码码字的自相关和组内码字间的互相关值仅在几个时间偏移处有附峰.理论推导与仿真结果相符.      

基于非正交码的波束形成网络幅相测试方法

针对目前数字波束形成网络幅相一致性测试系统中扩频码受限于正交码的问题,提出了一种基于非正交码的数字波束形成网络幅相测试方法。基于非正交码的幅相测试精度受多址干扰影响,提出了使用解相关算法提高幅相测试精度的方法,该方法以噪声略有增加为代价消除了多址干扰。理论分析给出了幅相测试的理论下界,并分析了系统误差、通道间耦合对幅相测试精度的影响。仿真结果显示,当采用非正交码时,测试设备不使用解相关算法无法达到预设的精度要求;使用解相关算法后,基于非正交码的幅相测试可以达到理论下界,在带内信噪比为10dB条件下,幅相测试精度为±01dB/1°,可以满足实际系统需求。     

Cross-layer design of LT codes and LDPC codes for satellite multimedia broadcast/multicast services

According to large coverage of satellites, there are various channel states in a satellite broadcasting network. In order to introduce an efficient rateless transmission method to satellite multimedia broadcasting/multicast services with finite-length packets, a cross-layer packet transmission method is proposed with Luby transform （LT） codes for efficiency in the network layer and low density parity check （LDPC） codes for reliability in the physical layer jointly. The codewords generated from an LT encoder are divided into finite-length packets, which are encoded by an LDPC encoder subsequently. Based on noise and fading effects of satellite channels, the LT packets received from an LDPC decoder either have no error or are marked as erased, which can be mod- eled as a binary erasure channels （BECs）. By theoretical analysis on LT parameters and LDPC parameters, the relationships between LDPC code rates in the physical layer and LT codes word lengths in the network layer are investigated. With tradeoffs between the LT codes word lengths and the LDPC code rates, optimized cross-layer solutions are achieved with a binary search algorithm. Verified by simulations, the proposed solution for cross-layer parameters design can provide the best transmission mode according to satellite states, so as to improve throughput performance for satellite multimedia transmission.     

Turbo乘积码技术及其FPGA实现

介绍Turbo乘积码的基本概念,对chase译码算法、硬判决码字的可靠性计算、串行和并行迭代译码算法及其FPGA硬件描述语言的实现作了介绍和仿真,给出了仿真的译码性能曲线。     

一种新的Turbo译码算法及其仿真实现

通过对Turbo码的原有译码算法的研究和仿真,发现原译码算法延时较大、译码速率较低,为了改善译码性能,提高译码速率、减小译码延时,文章提出了一种新的译码算法,并进行了性能仿真和工程实现,证明这种译码算法具有良好的性能和实用价值,与原有译码算法比较,在性能上也有优越性。     

一种维特比译码改进算法的研究

介绍传统维特比译码算法的基本原理;根据卷积编码的原理,结合(2,1,7)卷积码的子网表,提出一种维特比译码的改进算法,仿真结果表明,改进算法是可行的;最后通过数据分析,得出该算法与传统的译码算法相比具有存储量小、译码延迟短的优点。该算法同样适用于其它的卷积编码。     

基于LDPC的编码PCM/FM系统及其性能分析

提出一种基于低密度校验码LDPC的编码PCM/FM系统,并对该系统的性能进行分析与仿真。首先介绍接近Shannon限的先进的信道编码技术———低密度校验码(LDPC)信道纠错编码原理和解码算法,而后给出基于LDPC的编码PCM/FM系统方案,最后详细分析并仿真该系统的性能,着重比较未编码、卷积编码和LDPC编码三种系统的性能差异,还对比LDPC的各种不同参数(编码长度、校验矩阵等)对系统性能的影响。仿真表明,基于LDPC的编码PCM/FM系统具有非常优异的纠错性能,比未编码PCM-FM系统性能高出6~8 dB,适合于PCM/FM遥测系统的应用。     

一种用于GPS集群车辆监控系统的纠错编码

GPS集群车辆监控系统是 GPS技术、集群移动通信技术和 GIS(地理信息系统 )技术的有机结合体。它利用集群无线移动通信系统进行数据传输 ,误码率较高。本文介绍了一种 (2 ,1 ,9)扩展卷积码 ,能在译码约束长度 2 0个码元内 ,纠正 2个码元的随机错误和 4个码元的突发错误     

Drogue detection for autonomous aerial refueling based on convolutional neural networks

Drogue detection is a fundamental issue during the close docking phase of autonomous aerial refueling(AAR). To cope with this issue, a novel and effective method based on deep learning with convolutional neural networks(CNNs) is proposed. In order to ensure its robustness and wide application, a deep learning dataset of images was prepared by utilizing real data of ‘‘Probe and Drogue" aerial refueling, which contains diverse drogues in various environmental conditions without artificial features placed on the drogues. By employing deep learning ideas and graphics processing units(GPUs), a model for drogue detection using a Caffe deep learning framework with CNNs was designed to ensure the method's accuracy and real-time performance. Experiments were conducted to demonstrate the effectiveness of the proposed method, and results based on real AAR data compare its performance to other methods, validating the accuracy, speed, and robustness of its drogue detection ability.