首页> 外文会议>2012 6th ESA Workshop on Satellite Navigation Technologies amp; European Workshop on GNSS Signals and Signal Processing. >An architecture for an embedded antenna-array digital GNSS receiver using subspace-based methods for spatial filtering
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An architecture for an embedded antenna-array digital GNSS receiver using subspace-based methods for spatial filtering

机译:使用基于子空间的方法进行空间滤波的嵌入式天线阵列数字GNSS接收机的体系结构

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This paper presents an architecture for an embedded multi-antenna digital GNSS receiver. A two-stage adaptive beamformer for interference suppression and Line-of-Sight (LoS) signal amplification is presented and analyzed w.r.t. to an efficient implementation on embedded receivers. Jammer signals are mitigated at pre-correlation stage whereas the LoS signals are amplified at post-correlation stage. The method is based on a subspace-based approach where filter coefficients are derived from the eigenvalues and -vectors of the covariance matrix. In the first stage, the covariance matrix is determined immediately from the digital antenna signals for interference mitigation and in the second stage, the matrix is computed based on the correlator outputs of each satellite in LoS. Dedicated buildingblocks for covariance matrix estimation and filtering are required for interference mitigation since this operation is computed on sampling rate. A fixed-point VHDL implementation and related costs in terms of logic-cell requirements on an FPGA are provided for both blocks. Eigendecomposition is computed on an embedded processor. The implementation of two decomposition algorithms (one for interference mitigation and the other one for LoS-signal amplification) are presented. Optimizations and costs in terms of processing-cycles on an embedded processor are provided.
机译:本文提出了一种嵌入式多天线数字GNSS接收器的架构。提出并分析了用于干扰抑制和视线(LoS)信号放大的两阶段自适应波束形成器。在嵌入式接收器上的高效实现。干扰信号在前相关阶段得到缓解,而LoS信号在后相关阶段得到放大。该方法基于基于子空间的方法,其中,滤波器系数是从协方差矩阵的特征值和-向量得出的。在第一阶段,立即从数字天线信号中确定协方差矩阵,以减轻干扰;在第二阶段,基于LoS中每个卫星的相关器输出来计算矩阵。缓解干扰需要用于协方差矩阵估计和滤波的专用构建块,因为此操作是根据采样率计算的。为这两个模块提供了定点VHDL实现以及FPGA上逻辑单元要求方面的相关成本。本征分解是在嵌入式处理器上计算的。提出了两种分解算法的实现方式(一种用于缓解干扰,另一种用于LoS信号放大)。提供了嵌入式处理器上处理周期方面的优化和成本。

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