The document proposes a robust location fingerprint called Signal Strength Difference (SSD) to address the heterogeneity of mobile devices for indoor localization. SSD is derived analytically and tested experimentally using different mobile devices under various wireless conditions. Experiments consider both Wi-Fi and Bluetooth devices for AP-based and MN-assisted localization. Results show that SSD-based localization algorithms like K Nearest Neighbor and Bayesian Inference perform better than other approaches in literature that aim to mitigate effects of hardware variations. SSD provides a more robust location fingerprint compared to Received Signal Strength across different device hardware.