Heterogeneous wireless sensor networks consist of some different types of sensor nodes deployed in a particular area. Different sensor types can measure different quantity of a source and using the combination of different measurement techniques, the minimum number of necessary sensors is reduced in LOCALIZATION problems. In this paper, we focus on the single source LOCALIZATION in a heterogeneous sensor network containing two types of passive anchor-nodes: Omni-directional and vector sensors. An omni-directional sensor can simply measure the received signal strength (RSS) without any additional hardware. In other side, an acoustic vector sensor (AVS) consists of a velocity-sensor triad and an optional acoustic pressure-sensor, all spatially collocated in a point-like geometry. The velocity-sensor triad has an intrinsic ability in direction finding process. Moreover, despite its directivity, a velocity-sensor triad can isotropically measure the received signal strength and has a potential to be used in RSS-based ranging methods. Employing a heterogeneous sensor-pair consisting of one vector and one omni-directional sensor, this study tries to obtain unambiguity estimation for the location of an unknown source in a three-dimensional (3D) space. Using a velocity-sensor triad as an AVS, it is possible to determine the direction of arrival (DOA) of the source without any restriction on the spectrum of the emitted signal. However, the range estimation is a challenging problem when the target is closer to the omnidirectional sensor than the vector sensor. The existence method proposed for such configuration suffers from a fundamental limitation, namely the LOCALIZATION coverage. Indeed, this algorithm cannot provide an estimate for the target range in 50 percent of target locations due to its dependency to the relative sensor-target geometry. In general, our proposed method for the considered problem can be summarized as follows: Initially, we assume that the target's DOA is estimated using the velocity-sensor triad’ s data. Then, considering the estimated DOA and employing the RSS measured by two sensors, we propose a computationally efficient algorithm for uniquely estimation of the target range. To this end, the ratio of RSS measured by two sensors is defined and, then, shown that this power ratio can be expressed as a monotonic function of the target range. Finally, the bisection search method is proposed to find an estimate for the target range. Since the proposed algorithm is based on bisection search method, a solution for the range of the target independent of its location is guaranteed. Moreover, a set of future aspects and trends is identified that might be interesting for future research in this area. Having a low computational complexity, the proposed method can enhance the coverage area mostly two times of that explored by the existence method. The simulated data confirms the speed and accuracy of developed algorithm and shows its robustness against various target ranges and different sensor spacing.