Deriving meteor stream properties from meteor count rate time series in a multi-observer network

A reliable characterization of meteor streams from radio forward scatter observations requires corrections for both the sporadic meteor background and the observational biases introduced by equipment sensitivity and station geometry. These effects are captured through station-specific Observability Functions (OFs). Building on the approach proposed by Steyaert et al. (2006), we present a generalized modeling framework that applies exponential stream activity profiles within a constrained least-squares fitting procedure to meteor count rate time series.

To reduce ambiguity in the inversion, particularly when data are sparse or noisy, the method includes assumptions about the shape of the sporadic background and imposes constraints such as non-negativity and zero sensitivity when the radiant is below the horizon. A key improvement over the original method is the extension to multi-station datasets, which helps distinguish between stream and background components by exploiting varying observation conditions.

We apply the technique to forward scatter data from the Geminids and σ-Hydrids, recorded between 9–18 December 2019, using two stations with different antenna setups and using different transmitters. The fitted models reproduce count rates within expected uncertainties and yield plausible estimates for stream peak timing and width. The resulting OFs and background profiles differ between stations, underscoring the method's sensitivity to geometry and local conditions. While promising, the method’s performance remains dependent on input assumptions and data quality. It offers a step toward more systematic processing of radio meteor time series in distributed and heterogeneous observation networks.

References:

Steyaert, C., Brower, J., Verbelen, F., 2006. A numerical method to aid in the combined determination of stream activity and Observability Function.