TITLE:
Sparsity-Based Direct Location Estimation Based on Two-step Dictionary Learning
AUTHORS:
Tingting Wang, Wei Ke, Gang Liu
KEYWORDS:
Dictionary Learning; Compressive Sensing; Direct Location; Time-Varying Channel; Quadratic Programming
JOURNAL NAME:
Communications and Network,
Vol.5 No.3C,
October
4,
2013
ABSTRACT: This paper proposes an adaptive sparsity-based direct position
determination (DPD) appoach to locate multiple targets in the case of
time-varying channels. The novel feature of this method is to dynamically
adjust both the overcomplete basis and the sparse solution based on a two-step
dictionary learning (DL) framework. The method first performs supervised
offline DL by using the quadratic programming approach, and then the dictionary
is continuously updated in an incremental fashion to adapt to the time-varying
channel during the online stage. Furthermore, the method does not need the
number of emitters a prior. Simulation results demonstrate
the performance of the proposed algorithm on the location estimation accuracy.