Marsis Ground Processing Overview and Data Analysis Approach M. Cartacci, A. Cicchetti, R. Noschese, S. Giuppi Madrid 11-06-2008.

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Presentation transcript:

Marsis Ground Processing Overview and Data Analysis Approach M. Cartacci, A. Cicchetti, R. Noschese, S. Giuppi Madrid

Main Radar Signal Characteristics The more important characteristics able to quantify the radar performances are:  Signal to Noise Ratio (SNR).  Side Lobe Level.  Range Resolution.  Azimuth Resolution.

SNR The SNR is the dynamic range between the surface power echo and the galactic noise level and describes quite well if the radar is working fine or not. In signals with low values of SNR is more difficult to reveal possible sub-surface echoes, because they can be hide by the noise. The SNR is strictly dependent from the environmental behavior conditions as :  Ionosphere attenuation  Ionosphere distortion  Magnetic fields (Faraday rotation)  Surface roughness

Effects of a decreasing SNR on a Signal detection

Side Lobe Level The Side Lobe Level is the difference (in dB) between the main signal lobe and the second lobe. A low Side Lobe level can hide sub-surface echoes too close to the surface. The Side Lobe level is strictly dependent from:  Weighting functions (Hanning for Marsis) Environmental behavior conditions as:  Ionosphere distortion  Surface roughness

Side Lobe Level 13 dB Range Resolution 1 μsec Best Side Lobe Level 32 dB Worst Range Resolution 1.7 μsec

Side Lobes can hide another signal

Range Resolution The Range Resolution describes the radar capability to reveal surface and subsurface features and layers, along the signal propagation path. The ideal range resolution is given by R = c/2B Where c is the light speed in the vacuum and B is the bandwidth of the transmitted signal. For Marsis R = 150 m in the vacuum. In effect the final resolution after the Hanning weighting is R 1 = R*1,7 = 255 m in the vacuum. Of course the resolution change again considering the subsurface echoes. In this case the light speed c depends on the dielectric constant of the material, and then c 1 = c/sqrt(ε). So R 2 = c 1 /2B = m or less.

Range Resolution Surface

Azimuth Resolution The Azimuth Resolution describes the radar capability to reveal surface and subsurface features and layers in the along track direction. The hypothetical Azimuth Resolution of a pulse limited radar as Marsis, is: R az = 2(sqrt(2HR)) = Km where H is the S/C altitude and R is the Range Resolution Using the synthetic aperture technique the R az decreases between the 5,5-10 Km.

Marsis Pulse Limited Footprint Marsis Synthetic Aperture Doppler Filter 0 Ground Track Azimuth Resolution Marsis Coverage Filter 1 Filter 0 Filter -1 Filter 1 Filter 0 Filter -1 Filter 1 Filter 0 Filter -1 Filter 1 Filter 0 Filter -1 Filter 1 Filter 0 Filter -1 Filter 1 Filter 0 Filter -1 Ground Track

Radar Performance Constraints The main constraints that can reduce the radar performances or complicate the signal interpretation are:  Ionosphere distortion  Ionosphere delay  Ionosphere attenuation  Magnetic fields effects  Surface roughness  Surface clutter

Marsis Ground Processing: L2 Processor The signals collected by Marsis during each orbit with the subsurface operative modes and transmitted to the ground are already compressed in azimuth (the only exception is SS2), so the main task of the L2 processor is to perform the Range Compression in the best way. In order to eliminate or, at least, reduce the effect of the Ionosphere distortion, the L2 processor performs a phase distortion correction using the Contrast Method algorithm.

Subsurface Modes available Actually almost the 100% of the subsurface data available are SS3 data. The reasons are the following: SS3 is the most flexible (2 frequencies and 3 filters). The monopole is too noisy so SS1, SS4 and SS5 can be used but with heavy limitations. The SS2 data are range compressed and multilooked on board so no on-ground operations are possible.

CONTRAST METHOD Reference Function FFT Doppler Filter 0 RANGE COMPRESSION LEVEL 2 FORMAT LEVEL 1B FORMAT ( 8 bit ) Data Decompression LEVEL 1B FORMAT ( 32 bit ) IFFT Phase Correction LEVEL 2 PROCESSOR

Mars Ionosphere Effects As it is well known if a radio-frequency pulse, of frequency f, propagates through a section of ionized medium with plasma frequency f p, it will be subject to an extra-phase shift with respect to the free-space propagation. In order to maximize the penetration depth, MARSIS frequencies are low and so very close to the plasma frequency. As a consequence the chirp code transmitted by Marsis suffers the following problems:  Signal delay.  Signal Phase distortion.  Signal attenuation.

Ionosphere Delay 3 MHz 4 MHz Delay Max  50 μsec SEA = 0°SEA start = -21,73°SEA end = 34,67° Orbit 5587

6 dB Power Loss Worst Resolution Worst SNR Ionosphere Distortion

Signal processed with the Contrast MethodSignal processed without the Contrast Method Orbit 5587, OST 2, f 0 = 3MHz, Lat 44,33°/66,78°, Lon -130,74°/-128,01°, SE -21,7°/-0,7°

Ionosphere Distortion Signal processed with the Contrast MethodSignal processed without the Contrast Method Orbit 5587, OST 3, f 0 = 4 MHz, Lat 66,96°/78,25°, Lon -128,01° / 26,34°, SE 0,9°/34,67°

Magnetic Fields Mars has no appreciable global intrinsic magnetic field, but the MGS has established that the planet has strong local magnetic fields, probably related to properties in the martian crust. Flux densities with strength exceeding 200 nT were measured at heights of 400 Km above the surface, but in some regions this influence arrive up to 700 Km. The interaction between the plasma frequency of the Ionosphere and the local normal magnetic field vector, can produce the so called Faraday Rotation Angle. The Faraday rotation can change the polarization angle of the linearly polarized Marsis radar signal, producing an attenuation. In the worst case, if the radar signal returns to the receiver with a polarization angle perpendicular respect to the signal transmitted, the attenuation is total.

Magnetic Fields

Surface Roughness The performances of a radar nadir looking as Marsis, can increase or decrease according to the surface behavior. If the surface is flat, and perpendicular to the radar pointing, the return echoes energy is concentrated towards the receiver direction, the main lobe is narrow and the SNR increases. If the surface is rough, the return echoes energy is spread in all the directions, the main lobe is wide and the SNR and the Range Resolution decrease. It is important to underline that the surface roughness depends on the wave length of the signal, so a surface can be rough for a band and not for another

Surface Roughness

If the surface is rough, another phenomenon can afflict the radar signal: the surface clutter. In some circumstances surface features as mountains, craters, hills, canyons and channels produce echoes that can be identify, at the beginning, as subsurface echoes. Surface Clutter

H x z y  Cross Track No ClutterClutter  = penetration depth (vacuum) ε = subsurface dielectric constant Danger zone Surface Subsurface Layer

Surface Clutter

30 μsec

Surface Clutter

Clutter & Roughness a deadly combination ORBIT 3921, OST 6, FRAME 61, BAND IIIORBIT 3921, OST 6, FRAME 80, BAND IIIORBIT 3921, OST 6, FRAME 99, BAND III

Finally Subsurface Layers!