To prevent potential hazards posed by fast-evolving drones, it is of importance to develop a radar system for drone detection. Frequency modulated continuous wave (FMCW) radars are widely used for that purpose. Heterodyne architectures are preferred for them to mitigate dc offset errors. Having said that, FMCW radars suffer from permanent leakage from the transmitter into the receiver. The leakage phase noise raises the total noise floor and limits the radar sensitivity. Here, we propose a stationary point concentration (SPC) technique in order to overcome the challenges. The SPC technique concentrates the leakage phase noise on a stationary point to alleviate the impact of the noise. The technique can be realized using digital signal processing without additional hardware. The results show that the proposed technique significantly lowers the noise floor.

This paper presents a novel polyphase-basis discrete cosine transform that can be used for challenges to observe heart rate (HR) variability and sudden changes of HR in short time. To succeed in the challenges, real-time measurement which requires a short window length is needed. As the window length decreases, however, increased main-lobe width (MLW) and sidelobe width (SLW) result errors in measuring HR. Unlike commonly used discrete Fourier transform (DFT), the proposed method is based on DCT, which improves the accuracy of measured HR even though the short window length is used for the real-time measurement of HR. We demonstrate that the DCT can give 2 times shorter MLW and SLW than the DFT can. To verify the proposed method, it is compared with well-known existing methods, arctangent demodulation and complex signal demodulation, which use the DFT. We measured HR using a 10.225-GHz continuous-wave Doppler radar. In each experiment, the window lengths of 3, 2, and 1.5 s were used to measure HR in real time. Experimental results show that the proposed method has lower mean and standard deviation of errors than the existing methods have.

In human body communication (HBC), the human body is used as a medium for transmitting data between devices as a replacement for wired and wireless technologies. The human body functions as an antenna in the low-frequency band used by HBC. Owing to this antenna function, electromagnetic waves radiating from electronic devices or wireless services cause electromagnetic interference (EMI) in HBC devices. This paper addresses such EMI in HBC devices. The interference signal caused by EMI was measured while the human subject, who was using an HBC device, was exposed to a general EMI environment at multiple sites. Using the interference model obtained from the measured interference signals, bit-error-rate degradation caused by the interference signal was simulated. The interference model presented in this paper can be effectively used to achieve reliable data communication in various HBC devices.

This paper 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 a FMCW PolSAR. The proposed signal processing algorithm is based on the range Doppler algorithm (RDA). We developed a FMCW PolSAR system that transmits triangular LFM signals, which are used less frequently than sawtooth LFM in a 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.

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.