Dynamic routing of signal in on-board computers to increase system reliability

Мұқаба

Дәйексөз келтіру

Толық мәтін

Ашық рұқсат Ашық рұқсат
Рұқсат жабық Рұқсат берілді
Рұқсат жабық Рұқсат ақылы немесе тек жазылушылар үшін

Аннотация

The paper presents a module of the device for searching the degree of optimal placement (DOPPS) for onboard computers, implementing hardware and software reorganization of the topology of the onboard computer subsystem responsible for determining the parameters of speed, altitude, and incident flow pressure under combined interference. The “early cutoff” algorithm on the Kintex-7 FPGA checks up to 1.2 · 106 routes in 0.55 μs and switches the channel in less than 0.72 μs, which satisfies the 1 μs limit established by DO-178C and ARINC 664. HIL tests showed a 15% decrease in the integral “perturbed cost” ΔL and an increase in the probability of successful transmission Ps to 0.96. At the same time, the dynamic power of the CPU decreased by 1.1 W, and the peak temperature of the crystal did not exceed 55 °C. The solution is suitable for serial implementation in UAVs and modernization of manned systems without modification of certified software.

Толық мәтін

Рұқсат жабық

Авторлар туралы

Kirill Ivanenko

Southwest State University (SWSU)

Хат алмасуға жауапты Автор.
Email: k.iwanencko@gmail.com
ORCID iD: 0009-0006-5125-3720
SPIN-код: 3300-6222

postgraduate student

Ресей, Kursk

Dmitry Borzov

Southwest State University (SWSU)

Email: borzovdb@mail.ru
ORCID iD: 0000-0001-7926-8349
SPIN-код: 2905-2172

Dr. Sci. (Eng.), Professor, Department of Computer Engineering

Ресей, Kursk

Vitaly Titov

Southwest State University (SWSU)

Email: titov-kstu@rambler.ru
SPIN-код: 1042-6379

Dr. Sci. (Eng.), Professor

Ресей, Kursk

Alexander Sizov

Southwest State University (SWSU)

Email: sizov1942@mail.ru

Dr. Sci. (Eng.), Professor

Ресей, Kursk

Әдебиет тізімі

  1. Bukirev A.S. Method for diagnosing aircraft on-board equipment based on machine learning. Proceedings of MAI. 2023. No. 133. (In Rus.)
  2. Dzhigan V.I. Adaptive signal filtering: Theory and algorithms. Moscow: Tekhnosfera, 2013. 528 p.
  3. Yeskin V.I., Poluektov S.P., Rubinov V.I. et al. Modeling of the altitude-speed flight parameter sensor for a maneuverable aircraft. Proceedings of MAI. 2014. Issue 80. (In Rus.)
  4. Ivanov V.F., Koshkarov A.S. Increasing the noise immunity of GLONASS consumer navigation equipment by integrating it with inertial sensors. Proceedings of MAI. 2017. No. 93. (In Rus.)
  5. Likhachev V.P., Sidorenko S.V. Noise immunity of the image autofocusing algorithm based on minimum entropy in a complex background environment. Proceedings of MAI. 2016. No. 99. (In Rus.)
  6. Nerovny V.V. Noise immunity of multi-system GNSS consumer equipment. Moscow: Nauchnaya kniga, 2018. 227 p.
  7. Nikitin A.V., Soldatkin V.V., Soldatkin V.M. Design and algorithms for processing information for the helicopter low airspeed measurement system in takeoff and landing modes. Proceedings of MAI. 2012. Issue 61. (In Rus.)
  8. Oleynik A.I. Algorithm for calculating true values of aircraft flight aerometric parameters. Aerospace Instrumentation. 2011. No. 1. Pp. 3–10. (In Rus.)
  9. Tyapkin P.S. Hardware and software complex for testing methods of blind signal processing in radio systems. Proceedings of MAI. 2023. No. 129. (In Rus.). doi: 10.34759/trd-2023-129-17.
  10. Anderson J., Brown L. Low-latency AXI4-Stream DMA controller for high-speed data acquisition. In: Proceedings of the 31st International Conference on Field-Programmable Logic and Applications (FPL). 2021. Pp. 167–174.
  11. Gomes S., Pomportes B., Wallaert M. A real-time air-data system with embedded Kalman filtering on reconfigurable hardware. Aerospace Science and Technology. 2020. Vol. 105. Art. 105989.
  12. Sharman R.D., Lane T.P. An overview of the clear-air turbulence forecasting problem and future challenges. Progress in Aerospace Sciences. 2016. Vol. 82. Pp. 46–73.

Қосымша файлдар

Қосымша файлдар
Әрекет
1. JATS XML
2. Fig. 1. Example diagram of a graph of an onboard computer subsystem with 5 nodes: Pitot, Static – sensors; wij – the base weight; δij – the increment

Жүктеу (113KB)
3. Fig. 2. The tree of route enumeration for N = 4: branches that are interrupted when their partial cost exceeds βLbest are marked in gray

Жүктеу (206KB)
4. Fig. 3. Logarithmic plot of “number of tested configurations K vs N”: curves for the full search N! and for the algorithm with a cutoff (β = 0.85)); the change in the exponential slope to the power of p ≈ 1.7 is visible

Жүктеу (187KB)
5. Fig. 4. Surface ΔL(λice, λturb) for the base and optimized topology

Жүктеу (328KB)
6. Fig. 5. Structural diagram of UPSOR

Жүктеу (84KB)
7. Fig. 6. Block diagram of the algorithm

Жүктеу (252KB)

© Yur-VAK, 2025

Лицензия сипаттамасына сілтеме: https://www.urvak.ru/contacts/