Automatic Detection and Identification of Underdense Meteors Based on YOLOv8n-BP Model

Every day, millions of meteoroids enter the atmosphere and ablate, forming a long plasma trail. It is a strongly scattering object for electromagnetic waves and can be effectively detected by meteor radar at altitudes between 70 km and 140 km. Its echo typically has Fresnel oscillation characteristics. Most of the traditional detection methods rely on determining the threshold value of the signal-to-noise ratio (SNR) and solving parameters to recognize meteor echoes, making them highly susceptible to interference. In this paper, a neural network model, YOLOv8n-BP, was proposed for detecting the echoes of underdense meteors by identifying them from their echo characteristics. The model combines the strengths of both YOLOv8 and back propagation (BP) neural networks to detect underdense meteor echoes from Range-Time-Intensity (RTI) plots where multiple echoes are present. In YOLOv8, the n-type parameter represents the lightweight version of the model (YOLOv8n), which is the smallest and fastest variant in the YOLOv8 series, specifically designed for resource-constrained scenarios. Experiments show that YOLOv8n has excellent recognition ability for underdense meteor echoes in RTI plots and can automatically extract underdense meteor echoes without the influence of radio-frequency interference (RFI) and disturbance signals. Limited by the labeling error of the dataset, YOLOv8 is not precise enough in recognizing the head and tail of meteors in the radar echograms, which may result in the extraction of imperfect echoes. Utilizing the Fresnel oscillation properties of meteor echoes, a BP network based on a Gaussian activation function is designed in this paper to enable it to detect meteor head and tail positions more accurately. The YOLOv8n-BP model can quickly and accurately detect and extract underdense meteor echoes from RTI plots, providing correct data for meteor parameters such as radial velocities and diffusion coefficients, which are used to allow wind field calculations and estimate atmospheric temperature.