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A capability of imaging the subsurface of planetary bodies in the solar system is key to understanding their history, composition, and evolution. Probing these sub-surface environments is vital to answering a number of priority questions such as “What were the initial stages, conditions and processes of solar system formation and the nature of interstellar mater that was incorporated?” in NASA Decadal Survey as well as closing Strategic Knowledge Gaps on the Moon, Mars, Phobos, and Deimos for future human explorations. Current Ground penetrating radar (GPR) architectures are based on microwave devices which limit the flexibility and adaptability of these instruments to accommodate unexpected sub-surface conditions. This rigidness can become particularly challenging for planetary missions where a GPR radar is being considered in places where the surface and sub-surface conditions are not well understood or modelled. With a traditional microwave GPR, the system parameters (resolution, penetration depth) must be committed to by design prior to flight, which may later prove to be sub-optimal. For example RIMFAX on NASA’s Mars 2020 rover contain many fixed-frequency or “fixed-tuning” components (RF filters, mixers, amplifiers, …) that greatly limit the potential to adjust radar parameters (frequency, signal waveform, bandwidth,…) in-situ, as that would require changing these fixed RF components (for example changing filters to different bands). To address this challenge in planetary GPR instruments, our team proposes to develop an all-digital, in-situ reconfigurable Ultra-WideBand (UWB) ground-penetrating radar based on CMOS system-on-chip technology. This CMOS all-digital radar would allow for essentially all radar parameters (except the antenna) to be programmable in-situ (as there is no fixed-frequency or fixed bandwidth hardware), allowing a GPR instrument to adapt to an encountered near/sub-surface environment. A second major challenge of GPR technology is the self-interference of the strong transmitted signal leaking into the receiver as the radar operates at long wavelengths with both transmitter and receiver placed in proximity. This self-interference limits the amount of power that can be transmitted without saturating the receiver, limiting the penetration capabilities of the instrument. To overcome this self-interference we propose to introduce a second signal pathway coupled directly to the receiver which is driven by a generative artificially intelligent network embedded inside the radar chip hardware. This AI network is tuned to generate and optimization a 180 deg phase copy of the Tx-to-Rx leakage which cancels out the power leakage into the receiver. This allows the radar to transmit more power without self-saturating via transmit to receive coupling, enabling far better penetration than a conventional GPR architecture. The proposed 36 month PICASSO effort will mature the all-digital artificial intelligent GPR instrument concept from its current TRL of 2 (basic functions demonstrated) to a complete breadboard-style instrument providing an exit TRL of 4. Science operation will be validated through both laboratory and modest outdoor fielded testing.
Enabling lower cost innovative remote sensing instrument development from concept through breadboard and demonstration
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