Increasing computing performance of ADCS subsystems in small satellites for earth observation
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(2) Outline • • • • • • • . Introduction ADCS challenges “Y model” approach for ADCS DelFFi ADCS modeling and simulation OBC Hardware selection ADCS software integration Conclusions 2.
(3) What does Earth Observation and Formation Flying have in common? 3.
(4) Challenging ADCS subsystem ü ü ü ü ü ü ü . Multiple attitude modes High pointing accuracy Precise three axis control algorithms High resolution data types from sensors Onboard sensor calibration Fault detection and correction onboard functions for autonomous operation . More complex software à improving OBC capabilities for ADCS 4.
(5) DelFFi Mission Statement “The DelFFi mission shall demonstrate autonomous formation flying and provide enhanced scientific return within QB50 from 2016 onwards, by utilizing two identical triple-unit Cubesats of TU Delft which further advance the Delfi-n3Xt platform.”. Source: SSE TU Delft. 5.
(6) DelFFi ADCS software development. “Y approach”. 6.
(7) DelFFi ADCS software development ADCS Model. OBC platform. ADCS SW Integration. 7.
(8) DelFFi ADCS simulation model ADCS Model. 8.
(9) DelFFi ADCS input requirements. VP: Velocity pointing 9.
(10) ADCS software architecture (initial). 10.
(11) DelFFi ADCS simulation model. 11.
(12) ADCS model profiling Goal: Identifying the most demanding blocks inside the ADCS model by measuring relative CPU time utilization during simulation, for later code acceleration with digital signal processor (DSP). Process Steps: • Implement ADCS simulation model in Simulink • Setup up the Matlab profiler to collect model performance data • Setup up the simulation environment for ADCS model • Run the model profiler • Analyze ADCS model performance data • Select most demanding model block for code acceleration with DSP 12.
(13) Simulation environment setup. 13.
(14) ADCS model profiling results Block Function. Number of calls. Attitude estimation (EKF). 110 000. Velocity Pointing mode. 110 000. Other OBC functions. 110 000. Percentage of relative CPU time usage during simulation. 52% 14% 34%. Other functions include: • Environment initialization • ADCS Mode determination algorithm • Other attitude modes (Safe and De-Tumbling) • Simulation Termination 14.
(15) DelFFi OBC selection OBC platform. 15.
(16) OBC architecture trade off OBC Requirements: • Code acceleration support • Build system support from open embedded community • I2C, SPI and UART support • Power efficient floating point unit performance w.r.t. FPGA • COTS available • Open hardware and software. Better computing performance. Multicore CPU. Heterogeneous SoC Beagleboard XM 16.
(17) Hardware Test bed Beagleboard XM: - COTS and open hardware/software platform - TI DM3730 SoC (ARM processor +Digital Signal Processor) - Build system support from embedded community (Yocto project) - Continuous integration support (Jenkins) 17.
(18) ADCS software build system. 18.
(19) Results on services and drivers support. Operating system size with all driver support is 18 MB. 19.
(20) DelFFi ADCS software development. ADCS SW Integration. 20.
(21) DelFFi ADCS architecture (final) Non Accelerated blocks. Accelerated block ADCS application. ADCS OBC 21.
(22) Communication inside ADCS application. Optimized buffer size for EKF requirements 22.
(23) Integration Results • EKF execution speedup of 5-10 times (based on baseline performance for FFT) • ADCS software footprint size is less than 20 MB (regular footprint is 100-200 MB) • Memory size for data exchange between ARMDSP was reduced to 64MB ( initially 128 MB) • Fully automated operating system image generation with Yocto project + Jenkins 23.
(24) Conclusions. • “Y approach ” was introduced and implemented for DelFFi ADCS software architecture exploration • Model profiling technique helped to identify and quantify computing demand for ADCS attitude estimation algorithm. • Using a build system (Yocto project) and continuous integration tools improved software productivity problem 24.
(25) Further Work. • Continue the work in the porting of Simulink model to BeagleBoard XM board • Compare ADCS performance with results from Flight Model OBC (Benchmark) • Continue to investigate on code acceleration in space software applications with heterogeneous onboard processors 25.
(26) Thank You for your attention!!! j.carvajalgodinez@tudelft.nl 26.
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