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.

Artificial Neural Networks and Deep Learning Techniques Applied to Radar Target Detection: A Review

Radar target detection (RTD) is a fundamental but important process of the radar system, which is designed to differentiate and measure targets from a complex background. Deep learning methods have gained great attention currently and have turned out to be feasible solutions in radar signal processing. Compared with the conventional RTD methods, deep learning-based methods can extract features automatically and yield more accurate results. Applying deep learning to RTD is considered as a novel concept. In this paper, we review the applications of deep learning in the field of RTD and summarize the possible limitations. This work is timely due to the increasing number of research works published in recent years. We hope that this survey will provide guidelines for future studies and applications of deep learning in RTD and related areas of radar signal processing.

Simulation and analysis of partial pulse remained jamming to HPRF PD radar

To solve the problem that the duty cycle of HPRF PD radar is not easy to use the general tow-and-pull jamming, a method of partial pulse remained jamming is proposed. Taking the transmitting signal of PD radar acquired by DRFM as an example, the jamming effect of the signal is simulated and analyzed. The results show that the jamming signal is modulated by the radar signal acquired by DRFM, the jamming signal generated has a strong correlation with the target Echo Signal, and it can effectively jam the HPRF PD radar with less power, which proves the effectiveness of the method.

Electromagnetic Occlusion Algorithm Based on FPGA and Panel Grouping and Its Optimization

With the development of digital signal processing and advanced algorithms, real-time signal processing based on FPGA and DSP is suitable for high-speed radar signal processing. With the rapid development of science and technology, war has entered the information age guided by high technology, and advanced science and technology has played a vital role in the trend of war. In recent years in the modern war, many countries invest a lot of research effort on the stealth technology, and advanced stealth technology can use a variety of technical means to alter or weaken the feature information of the target, confuse the enemy radar detection system effectively, reduce the chance of being detected to the largest extent, and prolong the lifecycle of aircraft and weapons. This research mainly discusses the electromagnetic occlusion algorithm and its optimization based on FPGA and panel grouping. The FPGA model selected for this study is XC6VLX240T-1FF1156I. Because the amount of data processed here is not very large, the cache part directly uses the on-chip storage resources of the FPGA, and the AD device is used to perform analog-to-digital/digital-to-analog conversion on the signal and perform digital up-down conversion. For a facet, it is necessary to first verify whether it is a bright facet and set the flag to mark it, then the facet needs to be occluded with the triangular facet marked as a bright facet, and all bright facets that have been marked need to be traversed. Open MP parallelization of the occlusion algorithm is as follows: The physical optics method is used to calculate the target RCS, and the focus of parallelism is placed on the part with a large amount of calculation. When using Open MP to design a program on a multicore computer, each group is assigned a thread to give full play to the core computing power. The total field is scattered and superimposed by each surface element. This part uses the parallel processing mode of Open MP, which allows the panel judgment in the group to be carried out at the same time. This part requires schedule to allocate resources and use different parallel mechanisms for different calculations to optimize debugging. In the angular range where there is multiple scattering at 0 ° ≤ φ ≤ 90 ° , the calculation results and the measurement results are in good agreement, and when the two planes are simulated with 1820 triangular faces, the fast multiple scattering in this paper only needs 4 minutes. This research has realized the general radar signal processing method based on FPGA structure, and the design has important engineering realization significance.

Deployment of the C-band radar Poldirad on Barbados during EUREC⁴A

The German polarimetric C-band weather radar Poldirad (Polarization Diversity Radar) was deployed for the international field campaign EUREC4A (Elucidating the role of clouds–circulation coupling in climate) on the island of Barbados where it was operated from February until August 2020. Focus of the installation was monitoring clouds and precipitation in the trade wind region east of Barbados. Different scanning modes were used with a temporal sequence of 5 min and a maximum range of 375 km. In addition to built-in quality control performed by the radar signal processor, it was found that the copoloar correlation coefficient ρHV can be used to remove contamination of radar products by sea clutter. Radar images were available in real time for all campaign participants and aboard research aircraft. Examples of mesoscale precipitation patterns, rain rate accumulation, diurnal cycle, and vertical distribution are given to show the potential of the radar measurements for further studies on the life cycle of precipitating shallow cumulus clouds and other related aspects. Poldirad data from the EUREC4A campaign are available on the EUREC4A AERIS database: https://doi.org/10.25326/218 (Hagen et al., 2021a) for raw data and https://doi.org/10.25326/217 (Hagen et al., 2021b) for gridded data.

DETECTION OF A HARMONIC SIGNAL AGAINST THE BACKGROUND OF A NONSTATIONARY GAUSSIANINTERFERENCE WITH COMPLEX SPECTRUM

Background. Modern radar stations for various purposes operate in the conditions of interference created by the imprints of the radar signal from the background surface, from metrological formations (precipitation, clouds, etc.) and artificial radiation sources. Ensuring the operation of the radar in such difficult conditions requires the construction of adaptive signal processing algorithms that have high efficiency and maintain them when changing signal-to-noise situations. Objective. The purpose of the paper is creation of an adaptive algorithm for detecting a harmonic signal against the background of spatially correlated interference and estimating its parameters. Methods. Construction of a two-dimensional autoregressive model of a mixture of correlated spatial noise and harmonic signal and application of the empirical Bayesian approach to the synthesis of an adaptive algorithm for detecting and evaluating signal and noise parameters. Results. A two-dimensional adaptive space-time algorithm for detecting a radar signal reflected from a moving target against the background of a space-correlated interference is synthesized. The analysis of the efficiency of the algorithm by the Monte Carlo method is carried out. Conclusions. It is shown that the empirical Bayesian approach is an effective working methodology in solving the problem of detecting a harmonic signal and estimating its parameters under conditions of interference with a complex frequency spectrum under different conditions of a priori uncertainty of their parameters.

Plasma Generator with Dielectric Rim and FSS Electrode for Enhanced RCS Reduction Effect

In this study, a method was experimentally verified for further reducing the radar cross-section (RCS) of a two-dimensional planar target by using a dielectric rim in a dielectric barrier discharge (DBD) plasma generator using a frequency selective surface (FSS) as an electrode. By designing the frequency selective surface such that the passbands of the radar signal match, it is possible to minimize the effect of the conductor electrode, in order to maximize the RCS reduction effect due to the plasma. By designing the FSS to be independent of the polarization, the effect of RCS reduction can be insensitive to the polarization of the incoming wave. Furthermore, by introducing a dielectric rim between the FSS electrode and the target, an additional RCS reduction effect is achieved. By fabricating the proposed plasma generator, an RCS reduction effect of up to 6.4 dB in X-band was experimentally verified.

Reconstruction of signal phases for signals closer than the DFT frequency resolution

Radar signal processing is a promising tool for vital sign monitoring. For contactless observation of breathing and heart rate a precise measurement of the distance between radar antenna and the patient's skin is required. This results in the need to detect small movements in the range of 0.5 mm and below. Such small changes in distance are hard to be measured with a limited radar bandwidth when relying on the frequency based range detection alone. In order to enhance the relative distance resolution a precise measurement of the observed signal's phase is required. Due to radar reflections from surfaces in close proximity to the main area of interest the desired signal of the radar reflection can get superposed. For superposing signals with little separation in frequency domain the main lobes of their discrete Fourier transform (DFT) merge into a single lobe, so that their peaks cannot be differentiated. This paper evaluates a method for reconstructing the phase and amplitude of such superimposed signals.