Interference signal localization is a critical aspect of modern communication systems, particularly in environments with dense signal traffic. As wireless technology continues to advance, the ability to accurately identify and mitigate interference becomes essential for ensuring reliable communication. Interference can degrade signal quality, reduce data throughput, and increase latency, adversely affecting user experience and system performance. This paper explores the use of software-defined radio (SDR) to build a testbed with antenna array to estimate the direction of arrival (DOA) of interference signals, facilitating effective localization and tracking. Accurate identification and mitigation of interference are essential for ensuring reliable communication, especially in the context of advanced technologies like 5G and IoT, where the demands on spectrum management are significant. This study evaluates several popular algorithms, including MUSIC, alongside other recently developed methods, under varying signal-to-noise ratios (SNR) and different multipath conditions. The performance of these algorithms is assessed in both UCA and uniform linear array (ULA) configurations, highlighting their effectiveness in real-world scenarios. By employing effective localization techniques, the research contributes to improved system optimization and resilience.