Ad-hoc networks of simple, omni-directional sensors present an attractive solution to low-cost, easily deployable, fault tolerant target tracking systems. In this paper, we present a tracking algorithm that relies on a real time observation of the target power, received by multiple sensors. We remove target position dependency on the emitted target power by taking ratios of the power observed by different sensors, and apply the natural logarithm to effectively transform to another coordinate system. Further, we derive noise statistics in the transformed space and demonstrate that the observation in the new coordinates is linear in the presence of additive Gaussian noise. We also show how a typical dynamic model in Cartesian coordinates can be adapted to the new coordinate system. As a consequence, the problem of tracking target position with omni-directional sensors can be adapted to the conventional Kalman filter framework. We validate the proposed methodology through simulations under different noise, target movement, and sensor density conditions.