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An ω-Free Accelerometer Array Method for 2-D Trajectory Reconstruction
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AI
DOI：10.1109/TIE.2023.3247782.png)
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Abstract
En 中文
A trajectory can be reconstructed by integrating acceleration and angular velocity (i.e., omega) sampled by a single inertial measurement unit (IMU), which consists of an accelerometer (ACC) and gyroscope (GYRO). To reduce the system power consumption, a GYRO-free-IMU (GF-IMU) method was proposed, which disabled the more power-consuming GYRO and utilized only an ACC array (AA) to obtain acceleration and calculate omega. To alleviate the error accumulation problem in the GF-IMU method, we previously proposed an omega-free ACC pair (OFAP) method which does not require the calculation of omega and can estimate the trajectory by solving a constrained optimization problem. However, the constrained problem makes it computationally expensive to generalize the proposed approach for different AA setups with more ACCs. To enhance the scalability and robustness of the system, this article proposes a new omega-free inertia-based method, namely, omega-free AA (OFAA), which transforms the constrained problem into an unconstrained one, and derives its scalable and computational-efficient closed-form solution. In both physical experiments and simulations, compared with conventional inertial methods, the proposed OFAA method has a lower trajectory-reconstruction error per distance traveled and is more robust to errors in raw inertial data, while still having a low energy consumption.
Keywords:
Trajectory
Gyroscopes
Inertial navigation
Global navigation satellite system
Closed-form solutions
Accelerometers
Transmission line matrix methods
Accelerometers (ACC)
inertial navigation
motion detection
sensor arrays
trajectory reconstruction
Journal
IF:
7.2
Papers:
1.8W
Citations:
9.8W