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Fault diagnosis and location play a pivotal role in expediting fault restoration and enhancing power system resilience. However, integrating distributed generation and diverse load profiles has led to more complicated distribution networks, intensifying fault diagnosis and location challenges. Hence, there is a need to transform traditional distribution networks into resilient active ones that actively guide and utilize distributed energy resources, possessing active control and operational capabilities. This paper comprehensively reviews fault diagnosis and location techniques in distribution networks, focusing on faulted line selection, fault section estimation, and accurate fault location. It provides an in-depth analysis of current fault diagnosis and location techniques, along with an assessment of their challenges, summarizing and evaluating the current research status at both local and international levels. To address existing fault diagnosis and location technologies limitations, a method utilizing micro-phasor measurement units (μPMUs) to enhance situational awareness and state estimation of active distribution networks is proposed. The paper also provides a comprehensive analysis of the optimized configuration strategy for achieving network observability and fault diagnosis using limited μPMU, in addition to comparing and analyzing the advantages and disadvantages of typical solution algorithms for the optimal PMU placement (OPP) problem. In response to extreme disturbance scenarios in active distribution networks, resilience enhancement strategies are proposed from three perspectives: fault prevention, fault response, and fault restoration. Finally, a summary and outlook on current research methods for fault diagnosis and location, as well as the challenges and future research directions in resilience enhancement strategies, are provided. [Display omitted] • Review fault diagnosis, section estimation, and accurate fault location methods. • Improving power system resilience through fault diagnosis and location. • Strategies using limited μPMUs to enhance distribution network situation awareness. • Comprehensive methods for power system resilience in extreme disasters. [ABSTRACT FROM AUTHOR]