High Accuracy Motion Detection Algorithm via ISM Band FMCW Radar

The conventional frequency modulated continuous wave (FMCW) radar accuracy range detection algorithm is based on the frequency estimation and additional phase evaluation which contains Fourier transform and frequency refining analysis in each chirp, so it has the disadvantages of being computationally expensive, and not being suitable for real-time motion measurement. In addition, if there are other objects near the target, the spectra of the clutter and the target will be adjacent and affect each other, making it more challenging to estimate the frequency of the target. In this paper, the analytical expression of the Fourier transform of the beat signal is presented and it can be seen that spectrum leakage makes the phase of Fourier transform no longer consistent with the real phase of signal. The change regularities of real and imaginary parts of Fourier transform are studied, and the corrected phase of ellipse approximation is given in the industrial, scientific, and medical (ISM) band. Accurate displacement can be obtained by accurate phase. The algorithm can filter the direct current (DC) offset which is mainly caused by stationary objects. The performance of the algorithm is evaluated by a radar system whose center frequency is 24.075 GHz and the bandwidth is 0.15 GHz; the measurement accuracy of displacement is 0.087 mm and the accuracy of distance is 0.043 m.

Developing of Algorithms Monitoring Heartbeat and Respiration Rate of a Seated Person with an FMCW Radar

With a radar working in the 24 GHz ISM-band in a frequency modulated continuous wave mode the major vital signs heartbeat and respiration rate are monitored. The observation is hereby contactless with the patient sitting straight up in a distance of 1–2 m to the radar. Radar and sampling platform are components developed internally in the university institution. The communication with the radar is handled with MATLAB via TCP/IP. The signal processing and real-time visualization is developed in MATLAB, too. Cornerstone of this publication are the wavelet packet transformation and a spectral frequency estimation for vital sign calculation. The wavelet transformation allows a fine tuning of frequency subspaces, separating the heartbeat signal from the respiration and more important from noise and other movement. Heartbeat and respiration are monitored independently and compared to parallel recorded ECG-data.

Dynamic Eigenimage Based Background and Clutter Suppression for Ultra Short-Range Radar

Background and clutter suppression techniques are important towards the successful application of radar in complex environments. We investigate eigenimage based methodologies such as principal component analysis (PCA) and apply it to frequency modulated continuous wave (FMCW) radar. The designed dynamic principal component analysis (dPCA) algorithm dynamically adjusts the number of eigenimages that are utilised for the processing of the signal. Furthermore, the algorithm adapts towards the number of objects in the field of view as well as the estimated distances. For the experimental evaluation, the dPCA algorithm is implemented in a multi-static FMCW radar prototype that operates in the K-band at 24 GHz. With this background and clutter removal method, it is possible to increase the signal-to-clutter-ratio (SCR) by 4.9 dB compared to standard PCA with mean removal (MR).

Applications of radar measurement technology using 24 GHz, 61 GHz, 80 GHz and 122 GHz FMCW radar sensors

This paper presents a review of radar applications in high-accuracy distance measurement of a target. The radars included in this review are frequency modulated continuous wave (FMCW) radar sensors operating in four different millimeter-wave frequency bands, namely 24 GHz, 61 GHz, 80 GHz and 122 GHz. The radar sensors are used to measure the distance of standard and complex targets in a short range of a few meters, thus indicating that the choice of target and the medium used for radar signal propagation also play a key role in determining the distance measurement accuracy of an FMCW radar. The standard target is a trihedral corner reflector in a laboratory-based free space measurement setup and the complex targets include a piston in an oil-filled hydraulic cylinder and a planar positioning stage used in micromachining. In each of these measurement scenarios, a distance measurement accuracy in micrometer range is achieved due to the use of a sophisticated signal processing algorithm that is based on a combined frequency and phase estimation method. The paper is concluded with a technical comparison of the accuracy achieved by the FMCW radars reviewed in this article with other related works.

Low-Complexity 2D-MUSIC for Joint Range and Angle Estimation of Frequency Modulated Continuous-Wave Radar

A pre-processing technique is proposed to reduce the complexity of two-dimensional multiple signal classification (2D-MUSIC) for the joint range and angle estimation of frequency-modulated continuous-wave (FMCW) radar systems. By using the central symmetry of the angle steering vector from a uniform linear array (ULA) antenna and the linearity of the beat signal in the FMCW radar, this preprocessing technique transforms 2D-MUSIC from complex values into real values. To compare the computational complexity of the proposed algorithm with the conventional 2D-MUSIC, we measured the CPU processing time for various numbers of snapshots, and the evaluation results indicated that the 2D-MUSIC with the proposed pre-processing technique is approximately three times faster than the conventional 2D-MUSIC.