In this paper, we present challenges and achievements in development and use of a compact ultrasonic Phased Array (PA) module with signal processing and imaging technology for autonomous non-destructive evaluation of composite aerospace structures. We analyse two different sets of ultrasonic scan data, acquired from 5 MHz and 10 MHz PA transducers. Although higher frequency transducers promise higher axial (depth) resolution in PA imaging, we face several signal processing challenges to detect defects in composite specimens at 10 MHz. One of the challenges is the presence of multiple echoes at the boundary of the composite layers called structural noise. Here, we propose a wavelet transform-based algorithm that is able to detect and characterize defects (depth, size, and shape in 3D plots). This algorithm uses a smart thresholding technique based on the extracted statistical mean and standard deviation of the structural noise. Finally, we use the proposed algorithm to detect and characterize defects in a standard calibration specimen and validate the results by comparing to the designed depth information.

In this paper, we present an adaptive uncoupled matching network to compensate any performance degradation of compact multiple-input multiple-output (MIMO) systems due to antenna mutual coupling effects and channel variations. This method varies the antenna terminal loads per symbol-block, based on a random search algorithm, to find an optimum termination network that maximizes the performance metric, such as received power and capacity. It uses the received signals (voltages across the resistances of the terminal loads) to estimate or calculate the performance metric, in order to include the total effects in the optimization process. By applying the random search algorithm, our method does not require any knowledge of the array parameters such as impedance matrix, or derivatives of the performance metric(s) unlike other optimization techniques. We demonstrate this scheme by performing simulations to optimize the capacity of a 3 × 3 MIMO considering different propagation scenarios. We observe significant mean capacity improvements (more than 2 b/s/Hz) for all assumed propagation scenarios, when receive array antennas are spaced close as 0.05λ and terminated non-identically.

Massive multiple-input multiple-output (MIMO) is a promising technology for next generation wireless communication systems (5G). In this technology, Base Station (BS) is equipped with a large number of antennas. Employing high resolution analog-to-digital converters (ADCs) for all antennas may cause high costs and high power consumption for the BS. By performing numerical results, we evaluate the use of low-resolution ADCs for uplink massive MIMO by analyzing Bit Error Rate (BER) performance for different detection techniques (MMSE, ZF) and different modulations (QPSK, 16-QAM) to find an optimal quantization resolution. Our results reveal that the BER performance of uplink massive MIMO systems with a few-bit resolution ADCs is comparable to the case of having full precision ADCs. We found that the optimum choice of quantization level (number of bits in ADCs) depends on the modulation technique and the number of antennas at the BS.

In this article, we present the challenges and achievements in development and use of a compact ultrasonic Phased Array (PA) module and imaging technology for autonomous nondestructive evaluation of composite aerospace structures. We analyse the state of composite components by processing full waveform (A-scan) information from PA, perform slicing and visualization of the data.We further accomplish the improvement of the axial (depth) resolution by proposing a new signal processing algorithm based on threshold improved wavelet transform (TIWT), that is able to separate overlapped echoes. This algorithm extracts a reference echo model from A-scans with no defect, and uses complex continuous wavelet transform and phase information of full waveform to estimate and localize echoes of each A-scan. The results of the proposed algorithm are validated by comparing them to the reference sample measures.

Beam alignment for millimeter wave (mm Wave) vehicular communications is challenging due to the high mobility of vehicles. Recent studies have proposed some beam switching techniques at Road Side Unit (RSU) for vehicle to infrastructure (V2I) communications, employing initial position and speed information of vehicles, that are sent through Dedicated Short Range Communications (DSRC) to the RSU. However, inaccuracies of the provided information lead to beam misalignment. Some beam design parameters are suggested in the literature to combat this effect. But how these parameters should be tuned? Here, we evaluate the effect of all these parameters, and propose a beam design efficiency metric to perform beam alignment in the presence of the estimation errors, and to improve the performance by choosing the right design parameters.