Compression Algorithms for High Data Volume Instruments on Planetary Missions: a Case Study for the Cassini Mission

We investigated data compression algorithms to boost science data return from high data volume instrumentson planetary missions, particularly outer solar system missions where every bit of data represents an engineeringtriumph of over severe constraints on mass (limiting antenna size) and power (limiting signal strength). We developeda methodology to (1) investigate algorithms to improve compression, and (2) to work with the science teams to evaluatethe effects on the science.Our algorithm for compressing the Cassini RPWS (Radio Plasma Wave Science) data achieved a factor of 5 improvementin data compression (relative to what the RPWS team was using), and our algorithm for the Cassini UVIS(Ultraviolet Imaging Spectrograph) Saturn data set achieved a much higher factor (70). In both cases, the investigatorson the science teams who evaluated our results reported that the science goals were not compromised. Ourcompression algorithm for ISS (Imaging Science Subsystem) images achieved on average a factor of 1:7 improvementin lossless compression compared to the original algorithm. We also evaluated the compression effectiveness ofJPL’s Fast Lossless EXtended (FLEX) hyperspectral/multispectral image compressor on Cassini’s VIMS (Visible andInfrared Mapping Spectrometer) data. FLEX lossless compression provides a factor 2 improvement over the originalcompression. We also explore a different range of lossy compression which can achieve an additional factor 2 to 5depending on the fidelity required.Our findings have implications for the design of future space missions, particularly with respect to antenna size andoverall Size, Weight, and Power (SWaP) budgets, by demonstrating strategies to implement better data compression.In addition to improved algorithms, we show that an iterative process involving real-time science team evaluation andfeedback to update the on-board compression algorithm is both essential and feasible. We make the case that a spacecraftfacility compressor hosting a toolbox of compression algorithms, available to all of the science instruments andsupported by a team of compression experts, conveys significant benefits. Beyond the obvious benefits of increasedscience return and faster playback, better data compression enables design trades between antenna size and number ofscience instruments on the payload.