A neuromorphic SLAM system shows potential for more efficient implementation than its traditional counterpart. We demonstrate a mixed-mode implementation for spatial encoding neurons including theta cells, vector cells and place cells. Together, they form a biologically plausible network that could reproduce the localization functionality of place cells. Experimental results validate the robustness of our model when suffering from variations of analog circuits. We provide a foundation for implementing dynamic neuromorphic SLAM systems and inspirations for the formation of spatial cells in biology.