High-resolution TOA estimation for IR-UWB ranging based on low-rate compressed sampling

Traditionally, high-precision TOA estimation for IR-UWB ranging relies on extremely high-rate sampling, which is difficult to implement with low-cost. In this paper, by introducing the newly emerging compressed sensing (CS) theory to the design of IR-UWB ranging system, low-rate sampling based high-precision TOA estimation is realized. The matching-pursuit search-back (MP-SB) algorithm for TOA estimation is proposed, which utilizes iterative search and threshold comparison to detect the 1st path from the compressed sensing measurements of the received ranging signal. The detection threshold in each iteration step is adaptively optimized. The performance of the proposed method is analyzed through simulations under IEEE 802.15.4a channel models. Results show that the proposed method can obtain high-precision ranging results with measurements far less than Nyquist-rate samples. Therefore, the proposed method serves as an alternative practical high-precision IR-UWB ranging method¹.