A novel and general parameterized fading model for the instantaneous received path power is presented, which accounts for both wide-sense stationary shadowing and small-scale fading. A method-of-moments parameter estimator is derived and implemented using a non-linear least-squares algorithm. Performance is explored by analysis and simulation under different noisy channel scenarios, and compared to exact Cramer-Rao bounds in the case of uncorrelated shadowing, and to idealized CR bounds, where shadowing and small-scale fading processes are assumed to be observed separately, in the case when shadowing correlation was not negligible.

Classical multilateration techniques for position estimation assume direct connectivity between land-reference nodes with known fixed locations and a node whose location we want to estimate so that range, and angle of arrival estimates can be readily obtained using channel observations. In the case of Ad-Hoc networking a mobile node may not have direct connectivity to any or some land-reference nodes and these multilateration techniques will be difficult to apply. This work uses a dead reckoning approach to derive a multihop maximum likelihood multilateration scheme based on connectivity between several land-reference nodes and a node of interest via multiple intermediate links. Performance of the proposed location estimation scheme is analyzed, via simulations, with respect to the number of available reference nodes, time and angle of arrival estimation accuracy at each node, node transmission range, and node density in the network. The algorithm is shown to outperform linearized multilateration techniques and to become insensitive to knowledge of nuisance parameters as the number of available land-references increases.

In this paper, we investigate the fundamental loss of ranging resolution using received signal strength indicator (RSSI) observations relative to unprocessed received signal (URS) measurements. Unlike previous work, this is done for a single propagation model that accounts for large-scale (log-normal) fading and small-scale (multipath) fading effects. Further, this contribution fully accounts for the temporal correlation of the log-normal attenuation and the multipath channel, which previous work has ignored. Cramer Rao bounds on the estimates of range give us a complete description of the effects of data reduction (through RSSI observations), multipath, and random attenuation on the estimates of range.