Parallel and Distributed Computing and Networks
Parallel and Distributed Computing and Networks
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并行和分布式计算和网络
DOI：
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发表时间：
2011
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通讯作者：
Luo Qi
中科院分区：
文献类型：
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作者：
Luo Qi
本文涉及基于噪声中信号处理（GASP）并在无线传感器网络中使用的通用方法构建的广义检测器（GD）。 GD决定一个观察值是否包含一个属于一个空间的多维信号，或者当存在未知复杂的高斯噪声时，它是否包含属于正交子空间的多维信号。我们在匹配的和不匹配的信号案例中评估了广义检测器的性能，我们的结果表明，对于恒定功率复杂的高斯噪声，如果信号与转向矢量匹配，则GD性能优于自适应匹配过滤器（AMF），即普遍的似然比测试（GLRT），自适应相干估计量（ACE）和自适应束形式正交排斥测试（流产）。
This paper is concerned with a generalized detector (GD) constructed based on the generalized approach to signal processing (GASP) in noise and employed in wireless sensor networks. The GD decides if an observation contains a multidimensional signal belonging to one space or if it contains a multidimensional signal belonging to an orthogonal subspace when unknown complex Gaussian noise is present. We evaluate the performance of the generalized detector in both the matched and mismatched signal cases Our results show that for constant power complex Gaussian noise, if the signal is matched to the steering vector, the GD performance outperforms the adaptive matched filter (AMF), the generalized likelihood ratio test (GLRT), the adaptive coherence estimator (ACE), and the adaptive beam-former orthogonal rejection test (ABORT).