MIMO Radar Parallel Simulation System Based on CPU/GPU Architecture

The data volume and computation task of MIMO radar is huge; a very high-speed computation is necessary for its real-time processing. In this paper, we mainly study the time division MIMO radar signal processing flow, propose an improved MIMO radar signal processing algorithm, raising the MIMO radar algorithm processing speed combined with the previous algorithms, and, on this basis, a parallel simulation system for the MIMO radar based on the CPU/GPU architecture is proposed. The outer layer of the framework is coarse-grained with OpenMP for acceleration on the CPU, and the inner layer of fine-grained data processing is accelerated on the GPU. Its performance is significantly faster than the serial computing equipment, and satisfactory acceleration effects have been achieved in the CPU/GPU architecture simulation. The experimental results show that the MIMO radar parallel simulation system with CPU/GPU architecture greatly improves the computing power of the CPU-based method. Compared with the serial sequential CPU method, GPU simulation achieves a speedup of 130 times. In addition, the MIMO radar signal processing parallel simulation system based on the CPU/GPU architecture has a performance improvement of 13%, compared to the GPU-only method.

A MIMO Radar Signal Processing Algorithm for Identifying Chipless RFID Tags

In this paper, the multiple-input, multiple-output (MIMO) radar signal processing algorithm is efficiently employed as an anticollision methodology for the identification of multiple chipless radio-frequency identification (RFID) tags. Tag-identifying methods for conventional chipped RFID tags rely mostly on the processing capabilities of application-specific integrated circuits (ASICs). In cases where more than one chipless tag exists in the same area, traditional methods are not sufficient to successfully read and distinguish the IDs, while the direction of each chipless tag can be obtained by applying MIMO technology to the backscattering signal. In order to read the IDs of the tags, beamforming is used to change the main beam direction of the antenna array and to receive the tag backscattered signal. On this basis, the RCS of the tags can be retrieved, and associated IDs can be identified. In the simulation, two tags with different IDs were placed away from each other. The IDs of the tags were successfully identified using the presented algorithm. The simulation result shows that tags with a distance of 0.88 m in azimuth can be read by a MIMO reader with eight antennas from 3 m away.

Research on the Design of Digital Signal Processing Algorithm Based on Spark Parallel Calculation

Digital signal processing as a key and difficult point of network technology research and development, currently commonly used content such as LabVIEW. But from a practical point of view, while these techniques can be used to process real-time signals, they can’t handle historical offline data. The Spark parallel computing studied in this paper can be used to process offline signals. Therefore, on the basis of understanding the development trend of Spark parallel computing framework, the distributed Mallat algorithm is analyzed based on Spark parallel computing engine, and the application performance of the corresponding algorithm is verified.

Review Paper on Innovation of Advanced Noise Reduction Technique for Better Audibility Process

Now a days there are many people affected by hearing loss that make them disabled as they cannot communicate properly .The main complaint of people with hearing loss is low ability to deduce speech in a noisy environment. Hearing aid is a delicate instrument, which can acquire, process and feedback realistic signal in real time. In this matter various apparent opposition matching algorithm, various filtering methods, digital signal processing algorithm and echo cancellation are developed and implemented. The purpose of this object is to develop the digital signal processing based platform for digital hearing aid technique, which is for the people with hearing impairment using the low cost fuzzy orange pi model. To Perform this Application fuzzy algorithm is used which is quite easy to implement and required less operative computation. The algorithms are performed using MATLAB language which gives the best clarity and simulated functionality over MATLAB. Keywords: Speech Recognition, Noise Reduction, SNR, Fuzzy Masking Technique

Оптимізація поляризаційно-доплерівської селекції малорозмірних об’єктів на тлі підстильної поверхні

Using the method of maximum likelihood, the optimal algorithm of polarization-Doppler selection of objects on the background of the underlying surface, hydrometeors, urban buildings from aerospace carriers of radio electronic equipment has been synthesized. To solve the problem polarimetric properties of the scattered electromagnetic radiation of natural environments and anthropogenic objects were analyzed.The functional-deterministic mathematical model of the useful signalis determined. When solving the optimization problem, the method of maximum likelihood functionality and likelihood functionality for correlated processes were used, which contains the inverse matrix of inverse correlation functions of the observation equation. The obtained signal processing algorithm includes operations of spectral resection of passive interference. Polarization compensation of passive interference is performed by a combination of interchannel subtraction of the reflected signals of different polarizations. The quasi-optimal features of the synthesized algorithm, which has an obvious physical value and is optimal in the absence of internal noise, are considered. Based on the obtained results, a block diagram of the polarization-Doppler noise compensator and selection of useful signals against the background of noise reflections from the earth's surface has been developed. The study of the physical characteristics of the elements of the polarization covariance matrix of interferences at a high level of correlation of reflections of passive interferences of different polarizations is conducted.Based on the obtained results, it is proposed to introduce indicators of efficiency of passive interference compensation and selection of useful signals. The results of the analysis of the obtained indicators depending on the coefficient of the ratio of variances of passive interference indicate the need to use the polarization differences between signals and interference for selecting objects against the background of the underlying surface. The results obtained can be used to create ground-based and aerospace-based radar systems for detecting moving objects and objects with pronounced polarization features.

EPILLOW: A FABRIC-BASED PRESSURE SENSOR ARRAY FOR TETRAPLEGIC PATIENT CALL DETECTION SYSTEM

Call bell systems play an essential role in patient and nurse interaction in hospitals and at homes. However, many hospitalized patients, especially patients with tetraplegia, cannot press a call bell button for assistance due to hand weakness or paralysis from the neck down. This problem has motivated developing a fabric-based multi-array pressure sensor as a call bell garment, named ePillow, that works by detecting the pressure pattern on a pillow surface where the patient is lying down. In this study, off-the-shelf materials were utilized to form: i) a fabric-based multi-array pressure sensor system, ii) an acquisition circuit along with an interface, and iii) a signal processing algorithm to acquire and interpret the sensor data. To ensure the functionality of the proposed ePillow, a color-coded mesh plot was developed to visualize the sensor data. The reliability of the system was tested with two individuals. The pressure profile of the proposed ePillow shows a comparable profile to that of the commercialized pressure sensor. Findings from this case study have demonstrated the ability to map the force on the surface of the pillow and subsequently the location of the force applied with 71% accuracy and 70% sensitivity.

Модернизация эхометода ультразвуковой дефектоскопии

The modernization of the echo method of ultrasonic flaw detection is considered, which differs in that in addition to the array of transducers in contact with the working (front) surface of the object, one or more receiving transducers on the lateral surface of the object are additionally used. This method of arranging the antenna arrays can significantly improve the resolving power, and in the case of using an antenna array on the lateral surface of the object, obtain additional information for imaging the internal structure of the object. In order to obtain the potential resolution, an ultra-wideband sounding signal with a Gaussian envelope is used in combination with an original signal processing algorithm, including summation, one-way limiting and multiplication of the received signals. Some practical recommendations are given in the work. Potential resolution in various directions has been assessed.

Research on Optical Fiber Sensor Signal Processing Technology Based on Variational Mode Decomposition and Singular Spectrum Analysis

To better apply the phase-sensitive optical time-domain reflectometer (Φ-OTDR) in projects with complex environments, given the problem of the low signal-to-noise ratio of the Φ-OTDR signal, a variational modal decomposition (VMD) is proposed. Signal processing algorithm combined with singular spectrum analysis. First, the equalization optimizer (EO) optimizes the VMD. The VMD decomposes the preprocessed signal into a multi-layer eigenmode function (IMF), selects the IMF component according to the correlation coefficient, and after the SSA noise reduction process, the signal Reconstruction to realize the noise reduction processing of the Φ-OTDR signal. Through experiments, it is proved that the relative mean square error (RMSE) of the method in this paper is lower than that of EO-VMD, and the noise reduction performance is better.