Research On Uncertainty Of RCS Based On Radar 3D Imaging

Radar cross section(RCS)measurement is an important means to detect stealth performance of equipment.The traditional measurement method is limited by the test distance and equipment,and the test cost is high.In recent years,an RCS measurement method based on radar near-field three-dimensional imaging has become a research hotspot because of its three-dimensional spatial resolution and not limited by far-field measurement criteria.The uncertainty analysis of RCS is to evaluate the influence of various error sources on RCS measurement,which is helpful to evaluate the measurement quality and improve the measurement method.At present,the uncertainty analysis of dynamic measurement and compact field measurement has been carried out.As a new way,the uncertainty analysis of three-dimensional imaging RCS measurement is in urgent need.IEEE 1502-2020 is the guiding standard of RCS uncertainty analysis,which provides the basic guiding principle for RCS measurement uncertainty analysis.Various measurement methods should at least evaluate the uncertainty sources specified by it.Based on a related research project and combined with IEEE1502-2020,this paper analyzes the uncertainty factors of RCS one by one,and completes the evaluation of uncertainty factors in 3D imaging measurement.The main work and contribution are as follows:(1)The influence of uncertainty factors on RCS measurement accuracy in 3D imaging measurement is studied,and the estimation of uncertainty is given.Aiming at the radiation factor,the radiation uncertainty of traditional RCS measurement is defined by radiation gain attenuation.In 3D imaging measurement,the radiation gain received by the target is a dynamic process.In order to evaluate the uncertainty,the average irradiance is derived.Simulation results show that the uncertainty increases with the decrease of beam width.Secondly,the imaging RCS measurement needs to retrieve the far-field RCS from the near-field image,which is different from the traditional measurement,so the image sidelobe is a new source of uncertainty.The simulation of the standard sphere shows that the measurement uncertainty caused by the sidelobe can reach 4d B,which has a significant impact on the RCS result.Then,the interaction between background and target(multipath effect)and the imbalance of orthogonal channels are analyzed.In 3D imaging measurement,these two items will lead to false targets in the image.When the false targets can be eliminated by spatial separation,the influence can be eliminated.The analysis of noise shows that the influence of these two factors is very small,usually less than 0.001 db,because the three-dimensional imaging RCS measurement is based on coherent accumulation.The analysis of polarization factors shows that the polarization uncertainty decreases with the increase of polarization isolation.(2)For the radiation and image sidelobe factors,the corresponding uncertainty suppression methods are proposed.Firstly,for the energy nonuniformity caused by irradiation,a suppression method based on comprehensive irradiation response is proposed.The comprehensive energy weighting of each pixel in the target area is obtained by traversing each scanning position,and then the image is corrected by the normalized weighting value.By comparing the RCS inversion results before and after correction,it is proved that the proposed method can effectively reduce the measurement uncertainty caused by irradiation.Aiming at the problem of sidelobe interference,a sidelobe suppression method based on Sparsity Bayesian Recovery via Iterative Minimum(SBRIM)is proposed.The position information of scattering center is obtained by SBRIM,and then the amplitude and phase information is obtained by pulse compression,and then the 3D image is obtained by coherent accumulation.Simulation result shows that the proposed method can achieve sidelobe suppression and reduce the uncertainty of RCS measurement.