Error Analysis of RCS Dynamic Measurement System

The radar cross section (RCS) is a fundamental electromagnetic parameter used to test a target. A high-precision RCS measurement system can ensure accurate results. In order to better improve the accuracy of dynamic target scattering cross-section measurements and enhance the data quality assessment of external field dynamic RCS, it is necessary to implement an advanced measurement system. This paper investigates the influence of the uncertain factors which contained in the radar dynamic target scattering cross-section measurement system through uncertainty analysis method based on RCS measurement principle. In this paper, we categorize RCS measurement system into the next three distinct subsystems: radar trans-mitting system, propagation link system and target receiving system and further explores the errors caused by influencing factors in each subsystem of the radar dynamic target scattering cross-section measurement system. We then construct an error propagation model using probability statistics methods and synthesize the measurement errors from each subsystem through this model, this allows us to obtain the uncertainty results of the actual RCS measurement process. To validate and refine the error transfer model, we combine the BP neural network with measured data and determine the error weight contribution of each subsystem. We verified that the error transfer model is consistent with experimental results, the model can determine the total uncertainty of the RCS measurement system and the weight associated with each uncertain factor. This provides guidance for error correction and improve the accuracy of the target radar scattering cross-section measurement results. Furthermore, the model is universally applicable and can be used in dynamic RCS measurement processes involving different radars and targets.