Fault Location is an important task for distribution network (DN) operators, specifically for modern systems with the penetration of inverter-based distributed generations (IBDGs) such as photovoltaic and type IV wind generators. Accordingly, numerous techniques have been suggested to pinpoint Fault Locations in power distribution systems with DGs. Traditional methods encompass three primary approaches: traveling waves, impedance-based methods, and artificial intelligence (AI)-based techniques. In this paper, an efficient and simple feature is extracted by evaluating the pros and cons of these techniques. First, the principles and fundamentals of these methods are elaborated. Then, by analyzing the performance of these schemes, an improved Fault Location method based on impedance estimation is introduced. The proposed method does not suffer from the inherent drawback of the impedance-based methods, which is the need to know the network structure, lines and load data, and voltage and current measurements along the feeder in multiple points. The proposed feature could be used in AI-based techniques, which considerably improves the accuracy and reduces their complexity. To verify the effectiveness of the proposed scheme, in addition to the mathematical proof, a various set of time-domain simulations are carried out. The results show that the proposed scheme provides effective performance in the presence of IBDGs under the Fault with different resistances at different Locations.