This letter considers multiuser time delay estimation in a sparse channel environment for radiolocation. The generalized successive interference cancellation (GSIC) algorithm is used to eliminate the multiple access interference (MAI). To adapt GSIC to sparse channels the alternating maximization (AM) algorithm is considered, and the continuous time delay of each path is estimated without requiring a priori known data sequences.

We present a low-cost UWB-based radiolocation system complying with the IEEE 802.15.4a specifications. To significantly reduce the required analog-to-digital converter speed, we employ the sampling down conversion technique. The matching pursuit algorithm combined with a lost sample restoration algorithm is derived for the UWB time of arrival (TOA) estimation. The simulation results of the proposed algorithm show that the TOA estimation accuracy approaches the multipath resolution under the NLOS channel.

Multipath is one of the major error sources that deteriorates tracking performance in global navigation satellite system (GNSS). In this letter, the orthogonal matching pursuit (OMP) algorithm is used to estimate multipaths which are highly correlated with the line of signal (LoS) signal. The estimated multipaths are subtracted from the received signal such that the autocorrelation function of the received signal is restored to optimize the tracking performance. The performance of the proposed technique is verified via computer simulations under the multipath environment of GNSS.

Localization is an important problem for Wireless Sensor Networks (WSN). The localization method can be categorized as range-free or range-based schemes. Since sensor nodes are usually cheap and small, the range-based schemes that require range measurement unit are unsuitable in WSN. The DV-hop algorithm is one of the range-free localization algorithms in which average hop-distance and hop counts are used for range estimation. But it requires heavy communication cost if the number of nodes increases in the network. Therefore, we propose a simple algorithm to reduce the communication cost and its performance is verified via computer simulations.

The GNSS receivers suffer from the multipath interference which is highly correlated with the line of sight (LoS) signal. Such interference results in tracking and ranging errors. In this paper, we propose a novel algorithm that can estimate the direction of arrival (DoA) of the LoS signal in the presence of highly correlated multipath interference. The proposed algorithm combines the matching pursuits algorithm for multipath estimation and the minimum norm algorithm for DoA estimation. An efficient combination of two algorithms yields reliable estimates of the DoA of LoS signal as demonstrated by computer simulations.

This paper considers a blind DS-CDMA data and channel estimation algorithm using a uniform circular array. The channels are assumed to be sparse and static during a short packet transmission period. The channel estimates for different users yield the explicit estimates of the angle and time of arrivals, which are used for radiolocation. Our algorithm employs three approaches to solve the problem. The generalized successive interference (GSIC) algorithm is used to eliminate the multiple access interference. Matching pursuit (MP) is applied to enforce the channel sparsity constraint. Per survivor processing (PSP) is then employed to jointly estimate the channel parameters and data symbols. By successfully incorporating them, we present the GSIC/MP/PSP algorithm. Its performance is demonstrated by computer simulations and compared to the GSIC/MP algorithm which requires training sequences.