This paper addresses the problem of shooter localization using a wireless sensor network of soldier-worn gunfire detection systems. If the sensor is within the field of view of the shockwave generated by the supersonic projectile, then using acoustic phenomena analysis, the gunfire detection system can localize the source of the incoming fire with respect to the sensor location. These relative solutions from individual gunfire detection systems are relayed to the central node, where they are fused to yield a highly accurate geo-rectified solution, which is then relayed back to the soldiers for added situational awareness. Detailed formulation of the fusion methodology presented here indicates that the multi-sensor fusion algorithm for soldier-worn gunfire detection systems is essentially a weighted nonlinear least-squares algorithm, which can easily be implemented using the Gauss-Newton method. The performance analysis of the proposed fusion algorithm through numerical simulations reveals that the fused solution is much more accurate compared to the individual best sensor solution and the simple averaged sensor solution. Since the proposed fusion algorithm requires consistent weighting of individual sensor solutions, a consistency-based weighting scheme is introduced to tackle the lack of reliability among sensor provided weights. Implementation of the proposed fusion scheme along with the consistency-based weighting scheme on experimental data further confirms the numerical results.