Range-Point Migration-Based Image Expansion Method Exploiting Fully Polarimetric Data for UWB Short-Range Radar

Ultrawideband radar with high-range resolution is a promising technology for use in short-range 3-D imaging applications, in which optical cameras are not applicable. One of the most efficient 3-D imaging methods is the range-point migration (RPM) method, which has a definite advantage for the synthetic aperture radar approach in terms of computational burden, high accuracy, and high spatial resolution. However, if an insufficient aperture size or angle is provided, these kinds of methods cannot reconstruct the whole target structure due to the absence of reflection signals from large part of target surface. To expand the 3-D image obtained by RPM, this paper proposes an image expansion method by incorporating the RPM feature and fully polarimetric data-based machine learning approach. Following ellipsoid-based scattering analysis and learning with a neural network, this method expresses the target image as an aggregation of parts of ellipsoids, which significantly expands the original image by the RPM method without sacrificing the reconstruction accuracy. The results of numerical simulation based on 3-D finite-difference time-domain analysis verify the effectiveness of our proposed method, in terms of image-expansion criteria

Weyl Spreading Sequence Optimizing CDMA

This paper shows an optimal spreading sequence in the Weyl sequence class, which is similar to the set of the Oppermann sequences for asynchronous CDMA systems. Sequences in Weyl sequence class have the desired property that the order of cross-correlation is low. Therefore, sequences in the Weyl sequence class are expected to minimize the inter-symbol interference. We evaluate the upper bound of cross-correlation and odd cross-correlation of spreading sequences in the Weyl sequence class and construct the optimization problem: minimize the upper bound of the absolute values of cross-correlation and odd cross-correlation. Since our optimization problem is convex, we can derive the optimal spreading sequences as the global solution of the problem. We show their signal to interference plus noise ratio (SINR) in a special case. From this result, we propose how the initial elements are assigned, that is, how spreading sequences are assigned to each users. In an asynchronous CDMA system, we also numerically compare our spreading sequences with other ones, the Gold codes, the Oppermann sequences, the optimal Chebyshev spreading sequences and the SP sequences in Bit Error Rate. Our spreading sequence, which yields the global solution, has the highest performance among the other spreading sequences tested

Parametric Wind Velocity Vector Estimation Method for Single Doppler LIDAR Model

Doppler lidar (LIght Detection And Ranging) can provide accurate wind velocity vector estimates by processing the time delay and Doppler spectrum of received signals. This system is essential for real-time wind monitoring to assist aircraft taking off and landing. Considering the difficulty of calibration and cost, a single Doppler lidar model is more attractive and practical than a multiple lidar model. In general, it is impossible to estimate two or three dimensional wind vectors from a single lidar model without any prior information, because lidar directly observes only a 1-dimensional (radial direction) velocity component of wind. Although the conventional VAD (Velocity Azimuth Display) and VVP (Velocity Volume Processing) methods have been developed for single lidar model, both of them are inaccurate in the presence of local air turbulence. This paper proposes an accurate wind velocity estimation method based on a parametric approach using typical turbulence models such as tornado, micro-burst and gust front. The results from numerical simulation demonstrate that the proposed method remarkably enhances the accuracy for wind velocity estimation in the assumed modeled turbulence cases, compared with that obtained by the VAD or other conventional method

4.5-/4.9-GHz-Band Selective High-Efficiency GaN HEMT Power Amplifier by Characteristic Impedance Switching

A 4.5-/4.9-GHz band-selective GaN HEMT high-efficiency power amplifier has been designed and evaluated for next-generation wireless communication systems. An optimum termination impedance for each high-efficiency operation band was changed by using PIN diodes inserted into a harmonic treatment circuit at the output side. In order to minimize the influence of the insertion loss of the PIN diodes, an additional line is arranged in parallel with the open-ended stub used for second harmonic treatment, and the line and stub are connected with the PIN diodes to change the effective characteristic impedance. The fabricated GaN HEMT amplifier achieved a maximum power-added efficiency of 57% and 66% and a maximum drain efficiency of 62% and 70% at 4.6 and 5.0GHz, respectively, with a saturated output power of 38dBm, for each switched condition

Microwave Characteristics of an Independently Biased 3-stack InGaP/GaAs HBT Configuration

This paper investigates various important microwave characteristics of an independently biased 3-stack InGaP/GaAs heterojunction bipolar transistor (HBT) monolithic microwave integrated circuit (MMIC) chip at both small-signal and large-signal operation. By taking the advantage of the independently biased functionality, bias condition for individual transistor can be adjusted flexibly, resulting in the ability of independent control for both small-signal and large-signal performances. It was found that at small-signal operation stability and isolation characteristics of the proposed configuration can be significantly improved by controlling bias condition of the second-stage and the third-stage transistors while at large-signal operation its linearity and power gain can be improved through controlling the bias condition of the first-stage and the third-stage transistors. To demonstrate the benefits of using such an independently biased configuration, a measured optimum large-signal performance at an operation frequency of 1.6 GHz under an optimum bias condition for the high gain, low distortion were obtained as: PAE = 23.5 %, Pout = 12 dBm; Gain = 32.6 dB at IMD3 = -35 dBc. Moreover, to demonstrate the superior advantage of the proposed configuration, its small-signal and large-signal performance were also compared to that of a single stage common-emitter, a conventional 2-stack, an independently biased 2-stack and a conventional 3-stack configuration. The compared results showed that the independently biased 3-stack is the best candidate among the configurations for various wireless communications applications

Super-Resolution Time of Arrival Estimation Using Random Resampling in Compressed Sensing

There is a strong demand for super-resolution time of arrival (TOA) estimation techniques for radar applications that can that can exceed the theoretical limits on range resolution set by frequency bandwidth. One of the most promising solutions is the use of compressed sensing (CS) algorithms, which assume only the sparseness of the target distribution but can achieve super-resolution. To preserve the reconstruction accuracy of CS under highly correlated and noisy conditions, we introduce a random resampling approach to process the received signal and thus reduce the coherent index, where the frequency-domain-based CS algorithm is used as noise reduction preprocessing. Numerical simulations demonstrate that our proposed method can achieve super-resolution TOA estimation performance not possible with conventional CS methods

Performance Evaluation of Variable Bandwidth Channel Allocation Scheme in Multiple Subcarrier Multiple Access

Multiple Subcarrier Multiple Access (MSMA) enables concurrent sensor data streamings from multiple wireless and batteryless sensors using the principle of subcarrier backscatter used extensively in passive RFID. Since the interference cancellation performance of MSMA depends on the Signal to Interference plus Noise Ratio of each subcarrier, the choice of channel allocation scheme is essential. Since the channel allocation is a combinatorial problem, obtaining the true optimal allocation requires a vast amount of examinations which is impracticable in a system where we have tens of sensor RF tags. It is particularly true when we have variable distance and variable bandwidth sensor RF tags. This paper proposes a channel allocation scheme in the variable distance and variable bandwidth MSMA system based on a newly introduced performance index, total contamination power, to prioritize indecision cases. The performance of the proposal is evaluated with existing methods in terms of average communication capacity and system fairness using MATLAB Monte Carlo simulation to reveal its advantage. The accuracy of the simulation is also verified with the result obtained from the brute force method

Numerical Simulation of Single-Electron Tunneling in Random Arrays of Small Tunnel Junctions Formed by Percolation of Conductive Nanoparticles

We numerically simulated electrical properties, i.e., the resistance and Coulomb blockade threshold, of randomly-placed conductive nanoparticles. In simulation, tunnel junctions were assumed to be formed between neighboring particle-particle and particle-electrode connections. On a plane of triangle 100×100 grids, three electrodes, the drain, source, and gate, were defined. After random placements of conductive particles, the connection between the drain and source electrodes were evaluated with keeping the gate electrode disconnected. The resistance was obtained by use of a SPICE-like simulator, whereas the Coulomb blockade threshold was determined from the current-voltage characteristics simulated using a Monte-Carlo simulator. Strong linear correlation between the resistance and threshold voltage was confirmed, which agreed with results for uniform one-dimensional arrays