The Cassini RADAR is a multimode instrument built both by NASA/JPL and ASI/Alenia Spazio. The instrument operates in radiometer-only, scatterometer, altimeter, and imaging modes. This paper will describe this interesting unique radar and how it will be used to collect data at Titan.

The Cassini RADAR’s altimetry mode has been successfully used for probing the depth and composition of Titan’s hydrocarbons seas. In May 2013, during the spacecraft’s 91stflyby of Titan (T91), the instrument demonstrates its capabilities as a radar sounder, presenting a unique opportunity to constrain direct measurements of the depth and composition of Titan’s second largest sea, Ligeia Mare. Later, observations of Kraken Mare and Punga Mare were planned and executed in August 2014 (T104) and January 2015 (T108), respectively. While most of the seafloor was not detected at Kraken, suggesting the sea was either too deep or too absorptive in these areas to observe a return from the seafloor, shallow areas near Moray Sinus did return subsurface detections. At Punga Mare, a clear detection of the subsurface was observed with a maximum depth of 120 m along the interrogated track of the sea. We will present an analysis of all three altimetric observations of Titan’s mare, as well a re-analysis of altimetry data acquired over southern Ontario Lacus. Depths measurements and liquid composition are obtained using a novel technique which makes use of radar simulations and Monte Carlo based inversions. Finally, we will show that the estimates obtained from the direct measurements described above can be used along with the RADAR’s active (i.e. Synthetic Aperture Radar) and passive (Radiometry) modes to generate bathymetry maps of areas not observed by altimetry.

. IntroductionCassini’s RADAR altimetry data enabled the investigation of suspended particles and nitrogen gas bubbles in Titan’s hydrocarbon lakes and seas. These bodies, composed primarily of methane and ethane with dissolved nitrogen, may contain inclusions such as water ice, organic particles (e.g., tholins, nitriles), and nitrogen gas. Solid particles can originate from atmospheric haze, fluvial erosion, or precipitation, and may accumulate through sedimentation or surface runoff. Nitrogen bubbles are thought to form via supersaturation processes, triggered by temperature changes or increased ethane concentration during rainfall, leading to nitrogen exsolution and bubble formation near the seabed [1-3].We present a methodology to constrain the size and density of both solid and gaseous inclusions using Cassini RADAR altimetric returns. A physical model based on Mie scattering and radiative transfer theory, compares modeled and observed surface-to-volume power ratios (SVR) to assess the inclusion detectability in Titan's liquid environments [4].Figure 1. Selected bursts from T91 altimetric observation acquired by the Cassini RADAR.2. Dataset, modelling and assumptionsWe analyze altimetric data from the Cassini RADAR acquired at Ku-band (13.78 GHz, λ = 2.17 cm) acquired during fly-by T91 (Fig. 1). The data were processed using the Cassini Processing of Altimetric Data (CPAD), including incoherent averaging and range compression [5]. To enhance the nominal 35-m resolution, we applied super-resolution (SR) method based via Burg algorithm [6,7], improving surface/subsurface peak separation.Nadir-looking radar observations in altimetry mode allow for the analysis of suspended inclusions in a homogeneous liquid medium. The received waveform enables surface, subsurface, and volume-scattered power measurement from which constrain inclusion size and density. With the objective of obtaining an expression for the Surface-to-Volume scattering power Ratio (𝑆𝑉𝑅), we model a liquid column containing uniformly distributed spherical particles and evaluate the volume backscattered power based on radiative equilibrium. Reflected and transmitted powers are defined using the surface Fresnel coefficient, dependent on the host dielectric constant, and a two-way transmissivity term. The total volume backscattering cross section includes both this transmissivity and the individual particle backscatter cross sections. Signal attenuation from particle scattering and absorption—mainly influenced by size and loss tangent—is also considered. The model assumes identical dielectric properties, no polarization or multiple scattering effects, and neglects shadowing, valid for particles smaller than the radar wavelength. The final expression, obtained for the case of a beam limited configuration, iswhere 𝑃𝑆 and 𝑃𝑉 are the power reflected by the surface interface and through the volume respectively, 𝜎𝑜𝑉 and 𝑘𝑒 are the volume backscattering and extinction coefficients , 𝜃3,𝑑𝐵2 is the antenna beamwith at -3 dB, 𝑧1 and 𝑧2 are the integration depths [4].Figure 2. Two of the selected altimetric observations acquired during fly-by T91 over Ligeia Mare, before and after super-resolution processing, in black and blue respectively. The area highlighted in green refers to the integrated waveform, while the gray one to the integrated noise.3. Methodology and SVR MeasurementSVR was measured using T91 data over Ligeia Mare, where a consistent seabed echo was detected at approximately 160 m depth [5]. To improve seabed detectability, windowing has applied to the waveform, leading to degradation of the range resolution and limiting the available integration window. This required the application of super-resolution techniques to widen the final integration window between the surface and the subsurface, as shown in Fig.2.The presence of volume scattering has then been evaluated by comparing the measured SVR with the integrated Signal-to-Noise Ratio (SNR𝑖𝑛𝑡). The measured vol

Recently, the Cassini RADAR has been used as a sounder to probe the depth and constrain the composition of hydrocarbon seas on Saturn's largest moon, Titan. Altimetry waveforms from observations over the seas are generally composed of two main reflections: the first from the surface of the liquid and the second from the seafloor. The time interval between these two peaks is a measure of sea depth, and the attenuation from the propagation through the liquid is a measure of the dielectric properties, which is a sensitive property of liquid composition. Radar measurements are affected by uncertainties that can include saturation effects, possible receiver distortion, and processing artifacts, in addition to thermal noise and speckle. To rigorously treat these problems, we simulate the Ku-band altimetry echo received from Titan's seas using a two-layer model, where the surface is represented by a specular reflection and the seafloor is modeled using a facet-based synthetic surface. The simulation accounts for the thermal noise, speckle, analog-to-digital conversion, and block adaptive quantization and allows for possible receiver saturation. We use a Monte Carlo method to compare simulated and observed waveforms and retrieve the probability distributions of depth, surface/subsurface intensity ratio, and subsurface roughness for the individual double-peaked waveform of Ligeia Mare acquired by the Cassini spacecraft in May 2013. This new analysis provides an update to the Ku-band a

Over the course of its mission, Cassini flew multiple times over Titan’s surface collecting altimetric data with its radar. We analyzed altimetric measurements collected by Cassini’s radar when flying on the same region as to correlate such measurements (i.e., a crossover) and look for differences in altimetry caused by either inaccuracies in the altimetric measurement, orbital reconstruction errors, or, more interestingly, the time-variable Titan’s shape. Indeed, in a crossover, the observed altimetry is expected to be the same, if not for a tidal signal. This allows us to test both the accuracy of the altimetric measurements and that of the orbital reconstruction. In addition, if the crossover measurements are accurate enough and the geometry is appropriate, it would in principle possible to determine the Love number h2, which describe the response of Titan’s exterior shape to the forcing impressed by Saturn. We identified a total of 11 pair of Cassini’s tracks over Titan in which we have an overlap of the radar footprints from different flybys. We report on our findings for Cassini altimetric crossovers at Titan. We tested the accuracy of altimetric data generated with different processing techniques: the first moment of the returned waveform, the threshold estimator, and the Maximum likelihood Estimator (MLE). The first two techniques can also be corrected for off-pointing angles. Preliminary results shows that the corrected threshold and corrected first moment estimators

The Cassini spacecraft performed several flybys of Saturn’s largest moon, Titan, collecting valuable data. During several passes, altimetric data were acquired. Here, we focus on altimetric measurements collected by Cassini’s radar when flying over the same region at different epochs in order to correlate such measurements (crossovers) and investigate differences in altimetry. In our study, we assess altimetric errors associated with three distinct methods for extracting topography from Cassini’s radar data: the maximum likelihood estimator (MLE), the threshold method, and the first moment technique. Focusing on crossover events, during which Cassini revisited specific areas of Titan’s surface, we conduct a detailed examination of the consistency and accuracy of these three topography extraction methods. The proposed analysis involves closely examining altimetric data collected at different epochs over identical geographical regions, allowing us to investigate potential errors due to the variations in off-nadir angle, relative impact, uncertainties, and systematic errors inherent in the application of these methodologies. Our findings reveal that the correction applied for the off-nadir angle to the threshold and first moment methods significantly reduces the dispersion in the delta difference at the crossover, resulting in a dispersion of the order of 60 m, even lower than what is achieved with the MLE (~70 m). Additionally, an effort is made to assess the potential of Cassi

Saturn's moon Titan was explored by the Cassini spacecraft from 2004 to 2017. While Cassini revealed a lot about this Earth-like world, its radar observations could only provide limited information about Titan's liquid hydrocarbons seas Kraken, Ligeia and Punga Mare. Here, we show the results of the analysis of the Cassini mission bistatic radar experiments data of Titan's polar seas. The dual-polarized nature of bistatic radar observations allow independent estimates of effective relative dielectric constant and small-scale roughness of sea surface, which were not possible via monostatic radar data. We find statistically significant variations in effective dielectric constant (i.e., liquid composition), consistent with a latitudinal dependence in the methane-ethane mixing-ratio. The results on estuaries suggest lower values than the open seas, compatible with methane-rich rivers entering seas with higher ethane content. We estimate small-scale roughness of a few millimeters from the almost purely coherent scattering from the sea surface, hinting at the presence of capillary waves. This roughness is concentrated near estuaries and inter-basin straits, perhaps indicating active tidal currents.

Saturn's largest moon, Titan, boasts organic chemistry that may hold clues to how life formed on the primitive Earth. The Cassini Mission, to be launched in October 1997, will explore Saturn and its moons, especially Titan. Mapping the surface of Titan will be accomplished with a radar instrument that acts as a 14 GHz synthetic aperture radar, microwave radiometer, altimeter, and scatterometer.

IntroductionThe Cassini RADAR altimeter (Ku-band, 13.78 GHz, λ ≈ 2.17 cm) provided the first and so far only direct sounding of Titan's hydrocarbon seas, revealing depths exceeding 160 m in Ligeia Mare and constraining the methane-dominated composition of its northern liquid bodies [1–3]. Bathymetric retrievals rely on detecting weak seafloor echoes following the dominant specular surface return. Conventional sidelobe mitigation through spectral windowing (e.g. Blackman tapering combined with Burg autoregressive extrapolation) suppresses sidelobes at the cost of degraded vertical resolution and reduced signal-to-noise ratio (SNR), limiting detections in shallow basins and near shorelines.We present a re-analysis of Cassini altimetry based on a two-stage processing pipeline that addresses surface dominance directly, without spectral tapering. The pipeline combines (i) a CLEAN-inspired coherent cancellation of the surface return and (ii) a high-resolution Delay/Doppler focusing of the residual subsurface signal. The joint approach preserves the native ~35 m vertical resolution while improving along-track resolution by nearly an order of magnitude. The complete workflow is illustrated in Fig. 1.Figure 1. Two-stage processing pipeline applied to Cassini RADAR altimetric data. Stage 1 (left): CLEAN-inspired coherent cancellation of the surface return. Stage 2 (right): subsurface-adapted Delay/Doppler processing of the residual bursts. The final products are a high-resolution radargram and an along-track bathymetric profile. MethodStep 1 — Coherent surface cancellation. For each altimetric burst, the internal calibration chirp—routed directly into the receiver and therefore carrying the full system impulse response—is used as a deterministic replica of the surface return. The complex amplitude, phase, and delay of the surface echo are estimated through cross-correlation between the range-compressed echo and the compressed calibration waveform. A scaled, phase-aligned, and delay-shifted replica of the surface return is then coherently subtracted from the complex waveform on a sample-by-sample basis through CLEAN iterations applied to all bursts. Unlike spectral windowing, this approach removes the dominant surface response without degrading the matched-filter resolution and therefore the SNR.Step 2 — Subsurface-focused Delay/Doppler processing. CLEAN-processed residual bursts are focused through a Delay/Doppler Algorithm (DDA) [4,5] adapted for the subsurface regime. The Doppler centroid is estimated within a delay window restricted to the seafloor return, suppressing residual surface contamination, and the burst is retuned to zero-Doppler frequency using SPICE-derived spacecraft state vectors to account for the hyperbolic Cassini flyby geometry. Range/Doppler curvature is then compensated, followed by antenna-gain correction applied selectively to Doppler bins above an SNR threshold, to avoid noise amplification in low-power subsurface regions. Incoherent multilook integration across Doppler-resolved bursts, combined with adaptive Wiener filtering, recovers the SNR loss associated with the reduced number of looks per burst. ResultsWe apply the pipeline to three Cassini altimetric tracks over Titan's polar terrains — T91 (Ligeia Mare), T108 (Punga Mare), and T126 (Winnipeg Lacus) — and present here Winnipeg Lacus as a representative case study. Results for Ligeia and Punga, including the recovery of the seafloor reflector in shallow regions previously inaccessible to conventional Burg+Blackman processing, will be shown in the accompanying poster.Winnipeg Lacus (T126). Winnipeg Lacus is a small polar lake (~78.5°N, 155°W) that lies near the Cassini detection threshold in conventional altimetric processing. After Stage 1, coherent cancellation suppresses the specular surface peak by more than 60 dB and reveals a continuous seafloor reflector across the full track. Stage 2 improves along-track resolution from the beam-limited footprint