This article develops the applicability of non-linear processing techniques such as Compressed Sensing (CS), Principal Component Analysis (PCA), iterativeadaptive Approach (IAA), and Multiple-input-multiple-output (M...
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This article develops the applicability of non-linear processing techniques such as Compressed Sensing (CS), Principal Component Analysis (PCA), iterativeadaptive Approach (IAA), and Multiple-input-multiple-output (MIMO) for the purpose of enhanced UAV detections using portable radar systems. The combined scheme has many advantages and the potential for better detection and classification accuracy. Some of the benefits are discussed here with a phased array platform in mind, the novel portable phased array Radar (PWR) by Agile RF Systems (ARS), which offers quadrant outputs. CS and IAA both show promising results when applied to micro-Doppler processing of radar returns owing to the sparse nature of the target Doppler frequencies. This shows promise in reducing the dwell time and increases the rate at which a volume can be interrogated. Real-time processing of target information with iterative and non-linear solutions is possible now with the advent of GPU-based graphics processing hardware. Simulations show promising results.
A new method based on the iterative adaptive algorithm(IAA)and blocking matrix preprocessing(BMP)is proposed to study the suppression of multi-mainlobe *** algorithm is applied to precisely estimate the spatial spectr...
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A new method based on the iterative adaptive algorithm(IAA)and blocking matrix preprocessing(BMP)is proposed to study the suppression of multi-mainlobe *** algorithm is applied to precisely estimate the spatial spectrum and the directions of arrival(DOA)of interferences to overcome the drawbacks associated with conventional adaptive beamforming(ABF)*** mainlobe interferences are identified by calculating the correlation coefficients between direction steering vectors(SVs)and rejected by the BMP ***,IAA is subsequently employed to reconstruct a sidelobe interference-plus-noise covariance matrix for the preferable ABF and residual interference *** results demonstrate the excellence of the proposed method over normal methods based on BMP and eigen-projection matrix perprocessing(EMP)under both uncorrelated and coherent circumstances.
This work presents the design of a frequency modulated continuous wave (FMCW) multiple-input multiple-output radar system with collocated antennas. A key part of this article is the modification and application of the...
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This work presents the design of a frequency modulated continuous wave (FMCW) multiple-input multiple-output radar system with collocated antennas. A key part of this article is the modification and application of the iterative adaptive algorithm (IAA) for digital beamforming to an FMCW radar system. The implemented system operates in the 2.4GHz Industry, Scientific and Medical band with 100MHz of bandwidth and consists of a transmit (TX) site with four antennas and a receive (RX) site with four antennas. The angular resolution is greatly improved from 15 degrees with the common delay-and-sum beamforming to only 5 degrees with IAA beamforming, which was verified by the results from a radar simulator and by a field test with the implemented hardware. The challenge of synchronisation and maintaining phase coherence in systems with remote TX and RX sites is also addressed by proposing a low-frequency clock and trigger distribution system. This approach allows for cost-efficient systems which can be distributed over longer distances.
A control scheme for heterogeneous transportation networks is presented. The methodology is based on the concept of the Macroscopic Fundamental Diagram (MFD) integrated with an adaptive optimization technique. The het...
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ISBN:
(纸本)9781467365963
A control scheme for heterogeneous transportation networks is presented. The methodology is based on the concept of the Macroscopic Fundamental Diagram (MFD) integrated with an adaptive optimization technique. The heterogeneous transportation network is first partitioned into a number of regions with homogeneous traffic conditions and well-defined MFDs. A macroscopic MFD-based model is used to describe the traffic dynamics of the resulting multi-region transportation system. A multivariable proportional integral (PI) feedback regulator is implemented to control the nonlinear system in real-time. The control variables consist of the inter-transferring flows between neighbourhood regions and the actuators correspond to the traffic lights of these areas (e.g. boundaries between regions). The recently proposed adaptive Fine-Tuning (AFT) algorithm is used to optimize the gain matrices as well as the vector with the set-points of the PI controller. AFT is an iterative adaptive algorithm that optimizes the values of the tuneable parameters of the controller (e.g. gains and set-points) based on measurements of a performance index (e.g. total delay) for different perturbations of the parameters. The overall control scheme is tested in simulation and different performance criteria are studied. The performance of a fixed-time policy is compared to the final controller that is obtained after the convergence of AFT.
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