Insect pests are a serious threat to food security in our country. Many migratory insects are agricultural pests, and their capacity for long-distance migration can cause, devastating, often unexpected, outbreaks of these pests. Insect radar is the most effective tool for observing insect migration and is playing an increasingly important role in monitoring the migration of insect pests and providing early warning of outbreaks. However, because traditional insect radar cannot accurately estimate various biological parameters it cannot accurately identify species. Recent innovations and developments in radar technology, however, make it possible to obtain sufficiently accurate biological parameters to reliably identify migratory insect species. This article reviews the methods of extracting multi-frequency and polarization scattering parameters from radar echoes and summarizes ways of deriving insect biological parameters from different patterns of electromagnetic scatter. It also compares and analyzes the accuracy of determining insect weight, body length, body width and wing-beat frequency based on different methods. Finally, the performance of five machine learning algorithms used to identify 23 migratory insect species, and the influence of measurement errors on the accuracy of species identification, is assessed and discussed. This review demonstrates the feasibility of using radar to achieve high-precision identification of migratory insect species.