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首页> 外文期刊>IEEE Transactions on Signal Processing >Focused detection via multiresolution analysis
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Focused detection via multiresolution analysis

机译:通过多分辨率分析进行集中检测

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In many applications, there are strong discrepancies between the signal models assumed in the design phase and the actual signals encountered in the field. These discrepancies penalize significantly the performance of the matched filter that is fine tuned to the preassumed conditions. We propose a geometric framework that designs, via wavelet multiresolution-based techniques, a receiver whose performance is to a large degree insensitive to these mismatches. We say that the receiver is a focused detector. The approach defines a signal set S that identifies the class of diverse conditions that are expected to arise. We illustrate the method in the context of multipath problems. The matched filter, which is a simple receiver, assumes that S is a singleton. When this is not the case, the matched filter experiences strong degradation. On the other hand, the optimal receiver for the signal set S is practically infeasible since it requires a multidimensional nonlinear optimization. The paper designs the focused receiver as a good compromise between these two extremes. We replace the signal set S by a linear subspace G-the representation subspace-that minimizes a measure of similarity with S. We choose G to be a multiresolution subspace. This choice resolves to satisfaction several issues. The subspace design is reduced to the design of a single shiftable scaling function, the similarity between S and G can be computed explicitly, and the focused receiver that computes the energy of the orthogonal projection on G is implemented by a bank of correlators matched to scaled/delayed versions of the reshaped scaling function followed by an energy detector. We assume that the transmitted signal is a sample of a random process. The signal set S becomes an ensemble of linear spaces. We introduce the modified deflection as the appropriate similarity measure. The paper details our algorithm, describes how to compute the modified deflection, and illustrates the performance results that can be obtained.
机译:在许多应用中,设计阶段假设的信号模型与现场遇到的实际信号之间存在很大差异。这些差异会严重影响微调至预设条件的匹配滤波器的性能。我们提出了一种几何框架,该几何框架通过基于小波多分辨率的技术来设计接收器,该接收器的性能在很大程度上对这些失配不敏感。我们说接收器是聚焦探测器。该方法定义了信号集S,该信号集S标识了预期会出现的各种情况。我们在多路径问题的背景下说明了该方法。匹配滤波器是一个简单的接收器,它假定S为单例。如果不是这种情况,则匹配的滤波器会严重退化。另一方面,信号集S的最佳接收器实际上是不可行的,因为它需要多维非线性优化。本文将聚焦接收器设计为这两个极端之间的良好折衷。我们将信号集S替换为线性子空间G(表示子空间),该子空间将与S的相似度最小化。我们选择G作为多分辨率子空间。这个选择解决了几个问题。子空间设计简化为单个可移位缩放函数的设计,可以显式计算S和G之间的相似度,并且通过与缩放比例匹配的一组相关器来实现计算G上正交投影能量的聚焦接收器。重塑缩放功能的/延迟版本,后跟一个能量检测器。我们假设传输的信号是随机过程的样本。信号集S成为线性空间的集合。我们引入修正的挠度作为适当的相似性度量。本文详细介绍了我们的算法,描述了如何计算修正后的挠度,并说明了可获得的性能结果。

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