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This paper presents a signal generator and a Digital Beamforming Receiver (DBR) with high phase control resolution and high beam control resolution, respectively. The signal generator is designed based on a Direct Digital Synthesizer (DDS) and a Phase Lock Loop (PLL). In the DDS-PLL signal generator, the conventional divider in PLL is replaced with a mixer, comb generator, and a doubler to utilize high phase control resolution of DDS (14bit, 0.022°) as it is and to synchronize the DDS-PLL signal generator with the entire system. In the DBR, the output signals of the DDS-PLL signal generators are used as the second Local Oscillator (LO) signal, and the beamforming technique is implemented through the change of the phase of the second LO signals. Also, for sophisticated beamforming, all signal generator components in the DBR are synchronized for generating same and fixed frequency and phase. Finally, the DBR has the same phase control resolution as the DDS, and the phase of each chain of the DBR can be adjusted up to 0.022° (14 bit). The DBR using the DDS-PLL signal generator is designed and fabricated. The DBR consists of a 1X8 array Tapered Slot Antenna (TSA) part, a 1st and 2nd frequency conversion part, a 1X8 data acquisition and combiner part, DDS-PLL signal generator part, and a reference signal generator part. The phase control performance of the DBR was verified by measuring the phase change of the chain in the DBR according to the DDS phase change. Also, to verify the beamforming performance of the DBR with high beam control resolution, the radiation pattern of the DBR when the angle of the main lobe was 0°, 0.2°, 0.4°, 15°, and 30° was measured in the 28GHz band. At the main lobe, the gain error is within 1dB and the beam angle error is within 0.2 degrees. The simulation results are in good agreement with the measured results. A high resolution beamforming performance is achieved in the DBR using the DDS-PLL signal generator.

Multipolarizations of micro-Doppler signature (MDS) were combined to classify the elevation angle of a drone by a convolutional neural network (CNN). We classified the drone's elevation angle based on the MDS, which depends on the elevation angle of the drone. To enhance the classification accuracy, we utilized micro-Doppler from multiple polarized radar signals. We utilized and analyzed four different polarizations for the receiver, namely, vertical/horizontal/right-handed circular polarization (RHCP)/left-handed circular polarization (LHCP), while the polarization for the transmitter was vertical. The four receivers with different polarizations were fully synchronized with Tx for accurate MDS measurement for each polarization. The radar data received from the multiple polarizations were combined for the classification algorithm based on CNN. The classification rate of the elevation angles of a drone was improved from 84.745% to 97.9% compared to a single polarization by using multiple polarizations.

We propose a drone classification method for polarimetric radar, based on convolutional neural network (CNN) and image processing methods. The proposed method improves drone classification accuracy when the micro-Doppler signature is very weak by the aspect angle. To utilize received polarimetric signal, we propose a novel image structure for three-channel image classification CNN. To reduce the size of data from four different polarization while securing high classification accuracy, an image processing method and structure are introduced. The data set is prepared for a three type of drone, with a polarimetric Ku-band frequency modulated continuous wave (FMCW) radar system. Proposed method is tested and verified in an anechoic chamber environment for fast evaluation. A famous CNN structure, GoogLeNet, is used to evaluate the effect of the proposed radar preprocessing. The result showed that the proposed method improved the accuracy from 89.9% to 99.8%, compared with single polarized micro-Doppler image. We compared the result from the proposed method with conventional polarimetric radar image structure and achieved similar accuracy while having half of full polarimetric data.

This article presents a novel signal technique for Ku-band automobile frequency-modulated continuous-wave fully polarimetric synthetic aperture radar (FMCW PolSAR) system using triangular linear frequency modulation (LFM). Our proposed system shows the first utilizations of triangular LFM for an FMCW PolSAR. The proposed signal processing algorithm is based on the range Doppler algorithm (RDA). We developed an FMCW PolSAR system that transmits triangular LFM signals, which are used less frequently than sawtooth LFM in an SAR sensor. Using a theoretical background, we describe its configuration and how it works. We propose the novel processing solution, which forms two kinds of single-polarization images from a raw data set and is suitable for our system. We obtained all four kinds of single-polarization images from two raw data sets while using the triangular LFM. In comparison, when using sawtooth LFM, we obtained the four images from four raw data sets by repeating the RDA four times. The proposed method simplifies the FMCW PolSAR system configuration and the processing algorithm. We collected FMCW PolSAR raw data from an experimentally equipped automobile while maintaining a constant speed on a highway. The proposed algorithm and system were validated by processing a high-resolution FMCW PolSAR image.

The development of radar technology for the detection of small drones is getting attention of researchers. In this work, the detection of drones using Ku-band radar system has been discussed. We ha...

We present a novel approach to internal calibration of a radar system. A Ku-band radar system with internal calibration paths is designed. Thermal drift of a system is mainly caused by active components, which are a high-power amplifier (HPA) and a low-noise amplifier (LNA). We aimed to reduce the drift using a learning algorithm with a gradient-descent method. Hardware offset factors and calibration factors are introduced for the process. In the learning algorithm, a penalty term is formed based on the analysis of local minimum points. The result verifies the proposed internal calibration method. Maximum deviations of gain are 0.0477 dB for the HPA and 0.0132 dB for the LNA. In addition, the maximum deviations of phase are 0.2481° for HPA and 0.0722° for LNA, respectively.

Radiation leakage of a global positioning system (GPS) module was investigated for a drone detection system by measuring the attenuation effect and long-range detection on the outside of a building. The GPS module consisting of the radio frequency components is essential to control the flight of a drone. There is an unavoidable leakage in the GPS module during operation, and the leakage signal from the GPS module was analyzed and detected with a high-sensitivity receiver. To analyze the leakage from the GPS module during operation, we obtained the whole frequencies of leakage signals and the radiation pattern of a drone with the GPS module in an anechoic chamber. From the data, we measured the leakage signals in an outdoor space. Through outdoor measurement, it was confirmed that the theoretical attenuation effect was consistent with the measured value with a distance variation. Finally, the GPS leakage in the drone was measured up to 950 m with a high signal-to-noise ratio (SNR) of 25 dB.

Depolarized fields inside a magnetodielectric sample interfere with the accurate measurement of sample characteristics in a cavity perturbation method. These depolarized fields occur due to the polarization of the test sample, depending on the volume and shape of the sample, in the electromagnetic field. To characterize the magnetodielectric sample more accurately, we proposed an advanced rectangular cavity (RC) perturbation method. In this method, we investigated the change in the resonant frequency and $Q$ -factor of a cavity which depends on the volume, and shape of the sample, and depolarized fields within the sample. The depolarizing factor for calculating the permittivity and permeability of the sample is derived by separating the uniform and depolarized fields within the sample when the sample is inserted in the cavity. These separations of fields play an important role to improve the measurement accuracy. The proposed unified RC perturbation technique is validated initially by measuring the resonant frequency and quality factor and then calculating the complex permittivity and permeability at the TE $_{10l}$ mode. The standard dielectric material (Al2O3) and magnetic material (YIG) samples are measured with the vector network analyzer. The measurement was performed when the magnetodielectric sample having various shapes and volumes inserted into the RC resonator. In comparison with the previous cavity perturbation methods, the permittivity and permeability have been calculated more accurately with various shapes of the test sample, and we also found that the ratio of the maximum sample volume to the cavity for various samples increases about 40%. Based on the proposed method, for a cube-shaped sample, we obtained the complex permittivity and permeability consecutively at each resonance mode without any physical relocation of the test sample. Therefore, the test sample is capable of continuous more accurate and more effective measurement in the desired frequency band without relocation using the proposed technique.

Given the rapidly growing drone market, the development of drone detection radars has become highly important to prevent drones from damaging lives and property. Frequency-modulated continuous-wave (FMCW) radars have been frequently used for drone detection. Among the architectures of FMCW radar, a heterodyne architecture that involves different local oscillators and produces beat signals at the IF stage has often been chosen. The FMCW radar, however, has a chronic problem called leakage. In an earlier study, we proposed the stationary point concentration (SPC) technique to improve the signal-to-noise ratio (SNR) of small drones by reducing the increase in noise floor caused by leakage. We demonstrated that the proposed technique increases the SNR of small hovering drones in the 1-D power spectrum. In this article, we newly analyze the practical problems in the heterodyne FMCW radar system. One is the 2-D noise floor increase in the range-Doppler (r-D) map due to the leakage, and the other is unwanted Doppler shifts. Then, we propose an upgraded theory and realization method of the SPC technique for the detection of the small moving drone by improving the r-D map. We prove that the proposed method not only reduces the 2-D noise floor by mitigating the leakage but also removes the unwanted Doppler shifts by the phase calibration. Consequently, we show that the proposed method increases the SNR of the small moving drone and corrects its velocity information at the same time in the r-D map.

The signal processing technologies of synthetic aperture radar (SAR) have been vastly studied as diverse measurement modes for various applications. One of the technologies is Video-SAR (ViSAR). It is a land-imaging mode where a sequence of images is continuously formed on the spotlight mode. We propose a new signal processing method to generate the multi-frames of ViSAR using Doppler shifting technique via sub-aperture processing. The method is based on our designed wide-angle antenna, which is a corrugated horn shape with low side lobe and Gaussian beam pattern. This wide-angle antenna receives a wide Doppler band along the azimuth direction. Based on the characteristics of the antenna, we separate the wide Doppler band into each chirp pulse signal. Each of these separated signals has a different center time. Through each chirp pulse signal in Doppler domain, the proposed method generates each frame of video at a high frame rate. The proposed ViSAR processing can show high efficiency with low computation and without a fixed coordinate system. Moreover, it can also visualize a wider area on stripmap mode than the conventional ViSAR mode, and can derive the video results based on Range Doppler Algorithm (RDA). These advantages can lead to reduce economic costs and simplify the operating ViSAR system. We have performed the practical experiments using X-band chirp pulse SAR system mounted on an airplane to verify the proposed method.