部分范数约束的稀疏恢复算法及其在单载波水声数据遥测中的应用

To solve the problem of single carrier underwater-acoustic-data telemetry, compressive sensing (CS) provides competitive performance of compression and recovery with low energy consumption. The primary objective of CS is to minimize the l₀ norm, which is an NP hard problem. Hence, the common methods were transferred to minimize l₁ norm. However, l₁ norm minimization provided a limited accuracy. A partial-norm-constraint (PNC) based sparse signal recovery method was derived, which adopted PNC as a zero attraction in a Lagrange method, to distribute the soft threshold for the non-zero taps. The proposed method is used for at-sea data telemetry.