| The probe of China’s first Mars exploration mission,Tianwen-1,has been successfully launched.The payload on it will carry out scientific exploration on the topography,soil characteristics,water ice,climate,ionosphere and physical fields of Mars.Different from other rovers landing on the moon and Mars,Zhurong Mars rover is equipped with a full polarimetric subsurface penetrating radar(FP-SPR)for the first time.The radar’s mission is to detect the soil thickness,shallow subsurface structure and water ice distribution in the inspection area,and obtain the living conditions and environmental information of Martian life.The traditional ground penetrating radar(GPR)transmits and receives electromagnetic waves through a set of monopole antennas for data acquisition,which can only obtain the single polarization data of the target,and cannot fully reflect the various properties of the target.The antenna of FP-SPR is composed of two antenna units.The two transmitting antennas alternately emit orthogonal polarimetric electromagnetic waves,and the two receiving antennas gate to receive the echoes of corresponding polarization mode,which can form the full polarimetric detection of four polarization modes.Compared with the amplitude,frequency,phase and other information obtained by traditional GPR,FP-SPR can also obtain the polarimetric properties of the target.Therefore,we can obtain more abundant target information by analyzing full polarimetric radar data.The exploration of water ice is an important way to explore life on Mars,and it is also an important scientific goal of China’s Tianwen-1 Mars mission.Studies have shown that the water ice on Mars is mainly distributed in the polar regions,but it may also exist subsurface in the middle and low latitudes.Radar has become an important equipment for Mars patrol exploration due to its non-destructive detection working mode and its working characteristics not limited by visible light.Before obtaining the measured data of Mars,according to the possible subsurface structure of Utopia Planitia(the landing area of the Zhurong rover),a model was established for numerical simulation,and an effective method was found to process the full polarimetric radar data,which is of great significance to obtain more abundant subsurface information from the measured data of Mars in the future.This paper is mainly introduced from the following aspects:1.Establish the subsurface structure model of Utopia Planitia.According to the possible subsurface structure of Utopia Planitia(the landing area of the Zhurong rover),a two-dimensional model of low-latitude regions and a three-dimensional model of low-and mid-latitude regions were established.The influence factors such as topographical fluctuations,rough interfaces,rocks,water ice and the variation of dielectric constant of different layers are added to the model.The above detailed information makes the model more realistic.2.Forward simulation of the FP-SPR based on the three-dimensional model of Utopia Planitia.Use the 3D finite difference time domain method to carry out forward simulation of the established 3D model,and obtain the full polarimetric radar data of four polarization modes of VV,HH,VH and HV.Then,Gaussian white noise is added to the data to simulate the background noise interference of the radar during patrol detection.3.Data processing of FP-SPR simulation data.Firstly,band-pass filtering and Kirchhoff integral migration are used to perform preliminary processing on the acquired simulation data.Then,Pauli decomposition and two-dimensional principal component analysis(2D-PCA)are introduced,and the two methods are applied to the initially processed full polarimetric radar data for denoising research.Pauli decomposition characterizes the effective reflection information by extracting the polarimetric properties of the reflector.The scattering mechanism of each reflector can be obtained from the RGB image synthesized by the target generation factors representing the three scattering mechanisms.By changing the color allocation method of the RGB image,the position information of the abnormal bodies can be highlighted,and the interference of noise on the signal extraction can be reduced.2D-PCA reconstructs the original profile data matrix by selecting a set of optimal unit orthogonal vector bases which can represent the subsurface characteristics,so as to weaken the background noise and improve the data quality.Finally,by comparing and analyzing the denoising effect of the two methods,it is concluded that the ability of 2D-PCA to pick up anomalies is slightly weaker than that of Pauli decomposition,but its advantage lies in that it does not destroy the structure of the original profile and retains the waveform signal in the profile.4.Distinguish subsurface rocks and water ice blocks.Since the electromagnetic waves produce frequency shifts when passing through interfaces with electrical differences,different types of abnormal bodies can be distinguished by the frequency shift of the reflected signal.Continuous wavelet transform(CWT)is introduced to analyze the time-frequency distribution of the radar signal extracted by the 2D-PCA method.By analyzing the time-frequency characteristics of the reflected signals from rocks and water ice blocks,it is found that the peak frequencies of the two are different.The peak frequency at each time point is used to represent the dominant frequency,and the two-dimensional frequency distribution of the profile is obtained.Then the dominant frequency of the effective reflection signal is screened out according to the energy intensity of the signal,which is used to distinguish the abnormal bodies with different electrical parameters,indicating that CWT can effectively distinguish the subsurface rocks and water ice blocks. |
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