To identify potential man-made objects, traditional synthetic aperture radar (SAR) imaging techniques are used to consider the dependence in either frequency or azimuth domain. However, these existing methods may resu...
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To identify potential man-made objects, traditional synthetic aperture radar (SAR) imaging techniques are used to consider the dependence in either frequency or azimuth domain. However, these existing methods may result in inaccurate scattering estimation without utilising the inherent polarimetric diversity property. To improve the imaging performance, a polarimetric object-level SAR imaging algorithm is proposed. In the scheme, the polarimetric SAR imaging with canonical scattering characterisation is transferred into a simultaneous sparse approximation (SSA) problem by virtual of incorporating sparse representation and canonical shape feature model. Then the SSA problem is solved via an efficient l2, p-norm (p. (0, 1)) regularisation algorithm. The main advantages of the proposed method are twofold: (i) considering the dispersive, anisotropic and polarimetric scattering characteristics of scatterers allows for more accurate estimation of physically relevant scattering geometry information of scattering centres in comparison with the method ignoring polarisation dependence;and (ii) by exploiting joint sparsity of the multiple polarisation measurements, it can effectively enhance the recovery accuracy in the consistency of the canonical scatterers' number and locations in different channels. Experimental results are provided to verify the effectiveness of the proposed method.
Mode shape expansion is useful in structural dynamic studies such as vibration based structural health monitoring;however most existing expansion methods can not consider the modelling errors in the finite element mod...
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Mode shape expansion is useful in structural dynamic studies such as vibration based structural health monitoring;however most existing expansion methods can not consider the modelling errors in the finite element model and the measurement uncertainty in the modal properties identified from vibration data. This paper presents a reliable approach for expanding mode shapes with consideration of both the errors in analytical model and noise in measured modal data. The proposed approach takes the perturbed force as an unknown vector that contains the discrepancies in structural parameters between the analytical model and tested structure. A regularisation algorithm based on the Tikhonov solution incorporating the L-curve criterion is adopted to reduce the influence of measurement uncertainties and to produce smooth and optimised expansion estimates in the least squares sense. The Canton Tower benchmark problem established by the Elong Kong Polytechnic University is then utilised to demonstrate the applicability of the proposed expansion approach to the actual structure. The results from the benchmark problem studies show that the proposed approach can provide reliable predictions of mode shape expansion using only limited information on the operational modal data identified from the recorded ambient vibration measurements.
A bistable microwire reader is an inductive type sensor that measures the fast magnetic flux reversals in ferromagnetic microwires having predominant longitudinal magnetisation. The signal processing in such readers i...
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A bistable microwire reader is an inductive type sensor that measures the fast magnetic flux reversals in ferromagnetic microwires having predominant longitudinal magnetisation. The signal processing in such readers is a challenging problem due to short induced pulses, pile up effect, pickup noise, and ringing distortion in the pickup coils. In our present work, analog and digital reading schemes for multi-bit tags made of several bistable microwires have been proposed. The performance of an analog reader can be sufficient for well separated pulses. However, the digital algorithms deliver a clearer output signal with better pulse resolution in the case of the pulse pile up effect. In turn, this enables reliable code recognition. Here, two digital algorithms have been tested. The digital low-pass Gauss filter effectively suppresses the pickup noise and ringing oscillations. The deconvolution algorithm constitutes the inverse task with respect to the convolution operator defining the pickup voltage output. This algorithm recovers the initial pulse profiles and provides the highest possible resolution of a pulse series. The obtained results will be useful for the creation of a robust reader for bistable microwire tags that can be implemented in recycling projects, marking of items, and fraud protection. (C) 2010 Elsevier B.V. All rights reserved.
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