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The micro-Doppler (m-D) feature is regarded as a unique characteristic for target recognition. Sparse recovery based approaches for m-D parameter estimation using the single measurement vector (SMV) model have shown their effectiveness recently. However, SMV only fits for narrowband m-D signals, and accurate parameters can hardly be estimated using SMV in strong noise. The signals with the same sparse...
We proposed a novel blind polarization de-multiplexing technique for higher order modulation signals based on unscented Kalman filter (UKF) in 3D Stokes space. Simulation results show that UKF has better performance of de-multiplexing and convergence speed compared to extended Kalman filters (EKF).
Compressed Sensing (CS) theory has been widely used in radar signal processing field, and the reconstruction algorithm is the key to whether the original signal can be reconstructed from limited observations. However, the existing reconstruction algorithms either don't consider and remove the noise in signal reconstruction, or need the iterative estimation of noise variance during the signal reconstruction...
The external knee adduction moment (EKAM) is associated with knee osteoarthritis (OA) in many aspects including presence, progression, and severity of knee OA. Despite of its importance, there is a lack of EKAM estimation methods that can provide patients with knee OA real-time EKAM biofeedback for training and clinical evaluations without using a motion analysis laboratory. A practical real-time...
Multi-joint/multi-degree of freedom (DOF) human arm impedance estimation is important in many disciplines. However, as the number of joints/DOFs increases, it may become intractable to identify the system reliably. A robust, unbiased and tractable estimation method based on a systematic dynamics decomposition, which decomposes a multi-input multi-output (MIMO) system into multiple single-input multi-output...
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