GPS接收机捕获算法的研究

信号捕获是全球定位系统(global positioning syetem,GPS)接收机的关键技术,本文对GPS中的串行、匹配滤波和并行伪码相位三种捕获算法进行了理论分析,同时针对捕获算法的捕获时间、捕获运算量、占用资源以及捕获结果进行了对比分析和仿真验证。仿真分析表明:三种捕获算法均能有效捕获GPS信号,它们各有优缺点但并行伪码相位捕获方案更适合大规模推广,使用价值高。     

GLONASS卫星信号捕获研究

介绍了GLONASS卫星信号的组成和特点,分析了卫星导航接收机对卫星信号捕获的串行搜索算法,并介绍了基于快速傅里叶变换的并行频率和并行码相位捕获算法原理。对3种捕获算法的复杂度和捕获效率进行了对比分析,理论结果表明,并行码相位捕获算法效果较好。利用Matlab软件模拟产生GLONASS中频信号,对3种捕获算法进行了仿真验证。实验结果表明,在-25 dB的信噪比下,3种算法均能对1 ms卫星信号进行捕获,并行码相位捕获算法效率最高,与理论结果一致。     

基于FFT的GLONASS中频信号快速捕获算法

为了提高GLONASS中频信号的捕获速度,根据GLONASS信号捕获的特点,引入离散傅里叶变换进行相关运算,实现并行捕获。实验利用实际采集的GLONASS中频数据,将传统的串行捕获算法与基于FFT的快速捕获算法在Matlab上进行了对比。实验结果表明,基于FFT的快速捕获算法大大提高了运算速度,减少了捕获时间,捕获方法也得到改进。     

基于相关的SFFT的卫星信号捕获算法

GPS(Global Positioning System)接收机中,常用的捕获方法有时域串行捕获方法、基于FFT(Fast Fourier Transform)的并行频率捕获方法和基于FFT的并行码相位捕获方法,但在某些应用场景下,会对卫星信号的捕获速度提出更高的要求,因此给出了一种基于相关的SFFT(Sparse Fast Fourier Transform)的卫星信号快速捕获算法。该算法结合卫星信号伪随机码的强自相关性的特性,将原有的SFFT的幅度估值去掉,利用时域串行的捕获方法,将SFFT算法中输出的大值坐标点对应的本地伪码与接收卫星信号做相关,进而捕获卫星信号。通过实验对算法进行验证,并与已有的卫星信号捕获方法进行对比,结果表明该方法能有效地运用于卫星信号捕获中,并且该算法的运算量要比传统捕获算法更低。     

一种基于自动删除算法的PN码捕获技术研究

针对多径干扰对频率选择性信道下伪码捕获性能的影响,提出了一种基于自动删除算法的PN码捕获方法。该串行相关捕获系统通过一个基于排序数据方差的自动删除单元平均恒虚警检测器来删除参考滑窗中的干扰样本,并且不需要多径干扰数目的先验信息。对系统的平均捕获时间及检测性能进行了计算与仿真,与传统的自适应捕获方法相比,改进后捕获算法的性能得到较大的改善。     

基于淘汰判决的跳频同步捕获方案设计

跳频通信同步捕获方案中,串行自同步捕获方案与并行自同步捕获方案是目前应用最广的同步捕获方案,但是串行捕获方案同步捕获时间较长,并行捕获方案系统太复杂,对此提出了基于淘汰判决的同步捕获方案。从捕获时间、抗干扰性能以及系统复杂度3个方面评价了捕获方案的性能。实验结果表明,基于淘汰判决的捕获方案,在保证抗干扰性能与系统复杂度的同时,捕获时间约为串行自同步捕获方案的1/5。     

GPS信号捕获算法Matlab/Simulink仿真

为了评价GPS信号并行码相位捕获算法、并行频率捕获算法、线性捕获算法3种常见捕获算法捕获性能的优劣,采用Matlab/Simulink工具对其捕获效果进行仿真分析。首先理论分析三种捕获算法的优劣,再用Simulink模拟信号源,M文件实现捕获过程的方式,并以捕获时间作为标准,得出并行码相位捕获所用时间最短,并行频率捕获时间相对较长,线性捕获最慢的结果。这些算法的仿真实现和捕获性能的比较,对接收终端捕获模块的研发工作具有一定的参考与指导作用。     

基于软件的GPS信号捕获跟踪算法研究

对GPS软件接收机的捕获和跟踪部分进行了研究。对于捕获模块,通过对常用串行搜索捕获算法和并行频域搜索捕获算法的比较和分析,提出了一种新型并行码相位搜索捕获算法;对于跟踪模块,提出采用非相干延迟锁相环对码进行跟踪,同时采用Costas环对载波进行跟踪;最后,从捕获和跟踪的GPS信号中提取出导航电文,并根据电文中的参数计算出了用户的位置坐标,并在Matlab中对用户的位置坐标进行了定位解算验证。     

直接序列扩频系统中的捕获——一种方案的实现及其性能分析

论文提出了在直接序列扩频系统中将并行捕获和串行捕获相结合的伪随机序列捕获方案，介绍了该方案的实现，分析了该方案的性能，得出了采用该方案的平均捕获时间及其上限。     

GPS信号并行捕获中互相关干扰的消除

提出了一种新的算法-峰值相减法,用于在并行捕获中消除互相关干扰.仿真表明,该算法可以至少消除95%的互相关干扰,在整个定位算法的第一步消除互相关干扰,减轻了后面算法消除互相关干扰的负担,具有一定的实用性.     

A new approach to rapid PN code acquisition using iterative message passing techniques

Iterative message passing algorithms on graphs, which are generalized from the well-known turbo decoding algorithm, have been studied intensively in recent years because they can provide near-optimal performance and significant complexity reduction. In this paper, we demonstrate that this technique can be applied to pseudorandom code acquisition problems as well. To do this, we represent good pseudonoise (PN) patterns using sparse graphical models, then apply the standard iterative message passing algorithms over these graphs to approximate maximum-likelihood synchronization. Simulation results show that the proposed algorithm achieves better performance than both serial and hybrid search strategies in that it works at low signal-to-noise ratios and is much faster. Compared with full parallel search, this approach typically provides significant complexity reduction.     

Spread Spectrum PN Code Acquisition Using Hybrid Correlator Architectures

A hybrid correlator architecture is described which combines the serial structure of an active correlator with the parallel structure of a matched filter correlator. The mean PN code acquisition time performance of this hybrid serial-parallel correlator structure is analysed. Results are shown which compare the acquisition performance of the serial, parallel, and serial-parallel structures. The results are for a PN code length of 64 code chips and assumes a Gaussian channel with the receiver detection threshold set to obtain a constant false alarm rate. An enhancement to the serial-parallel acquisition algorithm is also described which can increase the acquisition time performance by about 15% for typical operating conditions. Overall the results demonstrate that the hybrid correlator can provide rapid code acquisition with a limited receiver complexity.     

A sequential multidimensional Cooley-Tukey algorithm

This work extends the serial/parallel and parallel/serial sequential FFT algorithms proposed, in the 1-D case by Singleton (1967) to the multidimensional (MD) case. MD sequential FFT can be profitably exploited for processing large data arrays that do not fit easily into the computer memory. Such situations are typical in image sequence analysis (for instance, it is quite common with television sequences). The MD sequential FFT retains the constant geometry characteristics of the Singleton algorithms, which is a feature that is very useful for implementation purposes     

微弱北斗信号捕获算法优化

恶劣环境中北斗卫星信号强度往往低于-133dBW,单周期捕获算法积分时间较短无法完成捕获,传统多周期捕获算法受二次编码和数据位翻转的影响易造成相关损失,限制积分时间的增长。半比特捕获方法虽能避免导航信息带来的位翻转,但是不能克服二次编码引入的位翻转;补零方法能够克服所有位翻转,但是不能实现长时间积分;树形算法通过尝试一定长度码片的所有可能符号组合,虽然能够有效延长积分时间,但随着码片数量的增加计算量呈指数上涨。针对北斗卫星信号中相干积分的时间受二次编码符号组合的限制问题,提出一种新的串并结合的算法,首先在一个周期的主码上进行串行搜索得到主码相位,而后在整周期二次编码上并行搜索确定二次编码的相位和多普勒频偏,达到延长相干积分时间实现微弱北斗信号捕获的目的,仿真证明在设定捕获阈值4dB时算法仍能够捕获-150dBm的信号。     

运动目标检测与特征提取算法的多层次并行优化

针对监控视频中运动目标实时特征提取的需求,在目标检测与特征提取串行算法的基础上,提出了基于OpenMP和多核CPU平台的三层并行优化算法。首先,在算法顶层,将串行算法抽象为两个模块组成的流水线,提出了流水线并行优化算法和相应的缓存管理策略;接着,在算法中层,考虑到特征提取模块中各子模块的功能独立性,设计了功能划分并行优化算法;最后,在算法底层,利用纹理特征提取模块的数据独立性,提出了数据划分并行优化算法。实验结果表明,该三层双模块并行优化算法在四核CPU平台上获得了接近Amdahl极限的加速比,基本实现了实际监控视频中运动目标检测与特征提取的实时处理。该多层次多模块并行优化方法普遍适用于串行算法在多核平台上进行并行优化的分析。     

Fault simulation on massively parallel SIMD machines algorithms,implementations and results

Two algorithms for fault simulation of combinational networks on massively parallel SIMD machines are presented. One algorithm uses a variant of the PPSFP [1] approach, while the other uses a mixture of parallel fault simulation [2] and PPSFP [1]. The algorithms have been implemented on the [Thinking Machines Corporation's] Connection Machine [3]. The second algorithm compares very favorably with published results for well known serial algorithms on the ISCAS benchmark circuits [4]. The results indicate that parallel processing could be a valuable tool for accelerating VLSI CAD applications.     

FDTD并行算法实现及其数据通信优化

应用计算机局域网,采用基于消息传递（MPI）方式和区域分割技术,实现了FDTD的并行计算。以无限长线电流源在自由空间辐射为算例,对并行FDTD算法进行了验证。结果表明并行算法和串行算法计算结果一致,并有效提高了计算效率。最后通过减少通信数据量、优化数据交换方式及通信和计算重叠的方法,使并行算法的数据通信得到优化,并行计算效率明显提高。     

Mean acquisition time analysis of fixed-step serial search algorithms

In this paper, mean acquisition time (MAT) analysis of fixed-step serial search (FSSS) algorithms is presented. First, it is shown that the MAT of an FSSS algorithm can be obtained from that of a conventional serial search (CSS) algorithm after a certain mapping of the uncertainty region. Then, a generic formula for the MAT of FSSS algorithms is derived, which is valid for both dense and sparse channel environments. In addition, MAT formulas for high signal-to-noise ratio scenarios, for large uncertainty regions, and for dense channels are obtained as special cases of the generic solution. Finally, simulation results are presented to verify the analysis and to investigate the factors that affect the optimal step size for FSSS algorithms.