Abstract: Unmanned agricultural equipment can effectively solve the shortage of labor force in recent years. Environmental perception has been one of the most important components to realize the safe and reliable operation of intelligent agricultural machinery in complex unstructured farmland. However, it is still limited in the environmental perception, due to the dynamic and unstructured environment. Some challenges also remained to enhance the autonomous cognition and coordination of unmanned agricultural machinery in the operations of "plowing, planting, managing, and harvesting". The perception sensors are also required to realize robust and real-time environmental safety. In this study, the stable and reliable technologies of environment information perception were reviewed to improve the autonomous navigation and operation performance of unmanned agricultural machinery. Firstly, the typical elements of unmanned agricultural machinery were introduced into the operating environment and various types of sensors. Then, the information perception technologies were summarized from the aspects of the obstacle, crop line, farmland boundary, and elevation information perception. Finally, the challenges and trends were summarized from the perceptual performance, open access dataset, multi-sensor data fusion, data standardization, and interface standard. The complex, changeable and unstructured environment was highly required for the robustness and real-time performance of the sensing system in the unmanned working. It was still lacking in the unified benchmarks of environmental perception and performance evaluation standards. New technologies were expected to overcome the current challenges. The finding can also provide strong support to the modernization and intelligence of agricultural production.