Evaluating target tracking protocols for wireless sensor networks that can localize multiple mobile devices, can be a very challenging task. Such protocols usually aim at minimizing communication overhead, data processing for the participating nodes, as well as delivering adequate tracking information of the mobile targets in a timely manner. Simulations on such protocols are performed using theoretical models that are based on unrealistic assumptions like the unit disk graph communication model, ideal network localization and perfect distance estimations. With these assumptions taken for granted, theoretical models claim various performance milestones that cannot be achieved in realistic conditions. In this paper we design a new localization protocol, where mobile assets can be tracked passively via software agents. We address the issues that hinder its performance due to the real environment conditions and provide a deployable protocol. The implementation, integration and experimentation of this new protocol and it's optimizations, were performed using the WISEBED framework. We apply our protocol in multiple indoors wireless sensor testbeds with multiple experimental scenarios to showcase scalability and trade-offs between network properties and configurable protocol parameters. By analysis of the real world experimental output, we present results that depict a more realistic view of the target tracking problem, regarding power consumption and the quality of tracking information. Finally we also conduct some very focused simulations to assess the scalability of our protocol in very large networks and multiple mobile assets.