An Elaborated Signal Model for Simultaneous Range and Vector Velocity Estimation in FMCW Radar

Abstract

A rigorous mathematical description of the signal reflected from a moving object for radar monitoring tasks using linear frequency modulated continuous wave (LFMCW) microwave radars is proposed. The mathematical model is based on the quasi-relativistic vector transformation of coordinates and Lorentz time. The spatio-temporal structure of the echo signal was obtained taking into account the transverse component of the radar target speed, which made it possible to expand the boundaries of the range of measuring the range and speed of vehicles using LFMCW radars. An algorithm for the simultaneous estimation of the range, radial and transverse components of the velocity vector of an object from the observation data of the time series during one frame of the probing signal is proposed. For an automobile 77 GHz microwave LFMCW radar, a computer experiment was carried out to measure the range and velocity vector of a radar target using the developed mathematical model of the echo signal and an algorithm for estimating the motion parameters. The boundaries of the range for measuring the range and speed of the target are determined. The results of the performed computer experiment are in good agreement with the results of theoretical analysis.

Low-Complexity Joint 3D Super-Resolution Estimation of Range Velocity and Angle of Multi-Targets Based on FMCW Radar

“…In the previous multi-dimensional joint estimation [22][23][24], matrix operations and multi-dimensional peak search are the main reasons for the high complexity. For coherent signals, smoothing is necessary [34].…”

“…Figure 7c shows the estimation process of G and V for two targets, Target 2 and Target 3; namely: Figure 7(c1) shows the estimated G of the two targets, and Figure 7(c2,c3) shows the corresponding estimated V for the two targets, respectively. Finally, through the 1D search of estimated G and V, the value of the peaks will be utilized to calculate the G and velocity for each target by the Equations ( 17) and (19), respectively, and then the estimated G and velocity for each target will be utilized to calculate the corresponding range and angle by the Equations ( 20) and (24). The final estimated results are listed in Table 1.…”

“…For example, the L-shaped, matrix or other shapes of receiving antenna array are used to implement the algorithm for joint super-resolution estimation of elevation and azimuth based on the two-dimensional (2D) MUSIC algorithm [20,21]. Additionally, the 2D MUSIC algorithm [22][23][24] achieves super-resolution joint estimation of range and angle by extending conventional 1D MUSIC for the angle domain to 2D MUSIC for the range-angle domain. However, the difficulty of this kind of algorithm in practice is that a lot of calculations are required in the process of constructing the covariance matrix and multi-dimensional peak searching; especially when the dimension is higher, the calculation amount is huge.…”

Location measurement of an object using radio networks for Industry 4.0 applications

“…The moment of signal arrival can be determined by the leading edge of the envelope of the received radio pulse, as well as by the cross-correlation between the envelopes of the received signals at the outputs of analog-to-digital converters (ADC). The second method provides greater positioning accuracy [14,20]. The signal processing circuit in the receiving device for the second option is shown in Figure 3.…”

A New Side-Looking Scheme for Speed Estimation and Detection of Tangential Slow-Moving Targets

“…Compared with traditional methods, radar sensors have the advantages of small size, light weight, low cost, and all-weather operation. Frequencymodulated continuous wave (FMCW) radar, which is widely used in traffic data collection, can measure speed by transmitting continuous waves (CWs) and comparing the beat frequency [9] or displacement difference [10] between the transmitted and received signals. As is known, the radial velocity of a moving object usually causes the frequency of the received signal to deviate from the carrier frequency, which is called the Doppler frequency [11,12].…”