TY - JOUR
T1 - A Flexible Air Data Sensing System-Enabled Real-Time Assessment of Full Flight Parameters
AU - Kang, Hui
AU - Gao, Yu
AU - Ke, Xin
AU - Li, Yunfan
AU - Jin, Biao
AU - Ma, Zhiqiang
AU - Jiang, Yonggang
N1 - Publisher Copyright:
© 1963-2012 IEEE.
PY - 2026
Y1 - 2026
N2 - Small drones operate in highly complex flight environments, necessitating miniaturized and low-cost flight-parameter sensing systems. Flexible air data sensing system (f-ADS) provides a new solution for the estimation of flight parameters. However, most current f-ADS systems only estimate airspeed and angle of attack (AOA), failing to achieve full flight parameter analysis, which is crucial for UAV flight. Here, we propose a low-cost f-ADS that integrates arrays of pressure, flow-velocity, and temperature sensors, aiming at the real-time decoding of full flight parameters with high precision. Using a near-sensor computing scheme, the f-ADS system achieves real-time estimation of full flight parameters, including airspeed, AOA, angle of sideslip (AOS), total air temperature (TAT), and pressure altitude (PALT) at 50 Hz. Wind-tunnel experiments showcase mean absolute errors (MAEs) of airspeed, AOA, and AOS of 0.25 m/s, 0.40°, and 0.34° within ranges of 10-30 m/s, ±16°, and ±8°, respectively. Field flight experiments demonstrate that the f-ADS responds promptly to attitude changes of the drone. The MAEs for airspeed, AOA, AOS, PALT, and TAT are 0.78 m/s, 0.54°, 0.78°, 1.57 m, and 0.15°C, respectively. These results show the potential application of f-ADS in the flight control of drones.
AB - Small drones operate in highly complex flight environments, necessitating miniaturized and low-cost flight-parameter sensing systems. Flexible air data sensing system (f-ADS) provides a new solution for the estimation of flight parameters. However, most current f-ADS systems only estimate airspeed and angle of attack (AOA), failing to achieve full flight parameter analysis, which is crucial for UAV flight. Here, we propose a low-cost f-ADS that integrates arrays of pressure, flow-velocity, and temperature sensors, aiming at the real-time decoding of full flight parameters with high precision. Using a near-sensor computing scheme, the f-ADS system achieves real-time estimation of full flight parameters, including airspeed, AOA, angle of sideslip (AOS), total air temperature (TAT), and pressure altitude (PALT) at 50 Hz. Wind-tunnel experiments showcase mean absolute errors (MAEs) of airspeed, AOA, and AOS of 0.25 m/s, 0.40°, and 0.34° within ranges of 10-30 m/s, ±16°, and ±8°, respectively. Field flight experiments demonstrate that the f-ADS responds promptly to attitude changes of the drone. The MAEs for airspeed, AOA, AOS, PALT, and TAT are 0.78 m/s, 0.54°, 0.78°, 1.57 m, and 0.15°C, respectively. These results show the potential application of f-ADS in the flight control of drones.
KW - Artificial neural network
KW - atmospheric data sensing system
KW - intelligent sensing
KW - multisensor fusion
KW - near-sensor computing
UR - https://www.scopus.com/pages/publications/105039316800
U2 - 10.1109/TIM.2026.3693792
DO - 10.1109/TIM.2026.3693792
M3 - 文章
AN - SCOPUS:105039316800
SN - 0018-9456
VL - 75
JO - IEEE Transactions on Instrumentation and Measurement
JF - IEEE Transactions on Instrumentation and Measurement
M1 - 9521009
ER -