Signal detection method having compression perception process based on orthogonal matching pursuit
An orthogonal matching tracking and compressive sensing technology, applied in baseband system components, transmission monitoring, electrical components, etc., can solve the problem of resource waste and achieve the effect of saving resources
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specific Embodiment approach 1
[0016] Specific implementation mode one: according to the instructions attached figure 1 Specifically illustrate this embodiment, the signal detection method with compressive sensing process based on orthogonal matching pursuit described in this embodiment, its detection process is:
[0017] Step 1: Set the preset number of iterations T, and set the margin r t The initial value of r 0 and the empty matrix V 0 , so that r 0 =y, then calculate the sensing matrix V=ΦΨ, where y is the sampling value, Φ represents the sampling process of compressed sensing, and Ψ represents the transform domain of the signal of interest s;
[0018] Step 2: According to the formula n t = arg t-1 , v i > selected in the sensing matrix V with a margin r t-1 The most correlated most correlated column vector v nt , where N is the number of columns in the sensing matrix;
[0019] Step 3: According to the formula V t =[V t-1 v nt ] update matrix V t-1 for V t , where V t Indicates the sen...
specific Embodiment approach 2
[0024] Specific embodiment 2: This specific embodiment is a further description of the signal detection method based on orthogonal matching pursuit with a compressed sensing process described in specific embodiment 1. According to the formula n described in step 2 of specific embodiment 1 r = arg t-1 , v i > selected in the sensing matrix V with a margin r t-1 The most correlated most correlated column vector v nt The specific process is: find the margin r in turn t-1 and each column v in the sensing matrix V i (i=1,...,N) inner productt-1 , v i >, the column vector number corresponding to the largest inner product is n t , 1≤n t ≤N, the column vector number n t The corresponding column vector v in the sensing matrix V i chosen as the margin r in the t-th iteration t-1 The most correlated most correlated column vector v nt , where N is the number of columns of the sensing matrix and the number of iterations t is a natural number less than the preset number of iterat...
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