Received radio frequency (RF) signal strength provides a cost-effective mechanism for distance estimation that is popularly used for range-based localization in wireless sensor networks (WSN). The typical method of determining sensor location using range-based localization methods is multilateration and this involves combining RSSI (received signal strength indicator) information from a number of beacons that is greater than the minimum number required for localization using accurate distance estimates. Multilateration using RSSI-based distance estimates are severely affected by shadowing and result in erroneous sensor location estimation. As a result of this, there was the need to come up with ways to overcome the effects of these shadowed measurements.The objective of this research is to minimize the effects of shadowing in sensor location estimation. To address this problem, several methods were explored. First, a scheme that applies a spatial correlation mechanism to eliminate RSSI signals that are affected by obstructions (i.e. shadowed signals) is presented. It is shown that the scheme is effective in minimizing the adverse effects of shadowing on RSSI signals hence sensor node localization. Next, outlier detection schemes were explored as a method to minimize the effects of shadowing. The effectiveness of the correlation-based localization scheme and the outlier detection schemes are validated using simulations and experimental data and have been shown to improve on sensor localization compared to other popular localization schemes.