The concept of wireless sensor network revolves around a group of sensor nodes that utilize the radio signals in order to communicate among each other. These nodes are typically made, of sensors, a memory, a multi-controller, a transceiver, and a power source to supply the energy to these components. There are many factors that restrict the design of wireless sensor network such as the size, cost, and functionality. The field of wireless sensor network, witnessed a remarkable revolution special after the environmental awakening in the last two decades. Its importance emanates from its capability to monitor physical and environmental conditions (such as sound, temperature, and pressure) with minimal power consumption. The principle of passing data cooperatively though a network to a main location played a vital role in the success of the methodology of WSN.This report explores the concept of wireless sensor network and how it is been made viable through the convergence of wireless communications and micro-electro-mechanical systems (MEMS) technology together digital electronics. The report addresses some of the factors that have to be considered when choosing the localization algorithm. It is very important to choose properly since the localization process may involves intensive computational load, based on many different criteria, as well as analysis method. The report also views the advantages and disadvantages of localization techniques. Nevertheless, it investigates the challenges associated with the Wireless Sensor Networks. The report categorizes the algorithms, depending on where the computational effort is carried out, into centralized and distributed algorithms. With minimal computational complexity and signaling overhead, the project aims to develop algorithms that can accurately localize sensor nodes in real-time with low computational requirements, and robustly adapt to channel and network dynamics. The report focuses on three areas in particular: the first is the Received Signal Strength indicator technique, Direction of Arrival technique, and the integration of two algorithms, RSS and DOA, in order to build a hybrid, more robust algorithms.In the Received Signal Strength (RSS), the unknown node location is estimated using trilateration. This report examines the performance of different estimators such as Least Square, Weighted Least Square, and Huber robustness in order to obtain the most robust performance. In the direction of arrival (DOA) method, the estimation is carried out using Multiple Signal Classification (MUSIC), Root-MUSIC, and Estimation of Signal Parameters Via Rotational Invariance Technique (ESPRIT) algorithms. We investigate multiple signal scenarios utilizing various antenna geometries, which includes uniform linear array (ULA) and uniform circular array (UCA). Specific attention is given for multipath scenarios in which signals become spatially correlated (or coherent). This required the use of pre-processing techniques, which include phase mode excitation (PME), spatial smoothing ...