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RF & MICROWAVE DESIGN Speed plus distance When using radar signals in such applications, developers generally want to simultaneously determine the speed and distance of multiple objects within a single measurement cycle. However, ordinary pulse radar cannot easily handle such a task. Based on the timing offset between the transmit and receive signals within a cycle, only the distance can be determined. If the speed must also be determined, a frequency-modulated signal is used, e.g. a linear frequency-modulated continuouswave (LFMCW) signal. The frequency offset between the transmit and receive signals is also known as the beat frequency. It has a Doppler frequency component fD and a delay component fT. The Doppler component contains information about the velocity, and the delay component contains information about the range. This equation has the unknowns of range R and velocity vr, and two beat-frequency measurements are needed to determine the desired parameters. Immediately after the first signal, a second signal with a linearly modified frequency is incorporated into the measurement. If there are multiple targets, however, it is no longer possible to unambiguously determine the beatfrequency pairs for several fast frequency changes (“chirps”). “Ghost targets” are generated that do not really exist. This problem can be solved using various transmit signals with different chirp rates, but the measurement time increases accordingly. Determination of both parameters within a single measurement cycle is possible with FM chirp sequences. Since a single chirp is very short compared with the total measurement cycle, each beat frequency is determined primarily by the delay component fT. In this manner, the range can be ascertained directly after each chirp. The Doppler frequency is neglected initially. However, if you determine the phase shift between several successive chirps within a sequence, the Doppler frequency can be determined using a Fourier transformation, making it possible to calculate the speed of the vehicles in front. The speed resolution improves as the length of the measurement cycle is increased. This complex process requires radar components that use state-of-the-art circuits and advanced signal processors with high processing power. Characterization of the radar signal Engineers working to develop radar sensors with LFMCW signals are faced with a major challenge: Any deviations from the ideal shape of the transmit signals cause errors in the determination of the velocity and range. Especially in safety-relevant Fig. 3 FM linearity can be well displayed with the R&S FSW using the spectrogram mode. Any deviations are clear at a glance. applications, this can have disastrous consequences. Important parameters such as the frequency linearity of a chirp, its length and its reproducibility within a chirp sequence must all be verified. Signals of this type with rapidly changing frequencies and wide bandwidths can be characterized using a time-domain signal analysis technique known as transient analysis. A spectrum analyser such as the R&S FSW from Rohde & Schwarz is suitable for this application. A transient analysis option designed for radar applications is available for this instrument. The option allows automatic detection and analysis of linear FM chirp sequences. Important chirp parameters such as the chirp rate, chirp length and chirp rate deviation are displayed in a result table, eliminating the need for manual analysis with marker functions. I/Q-based data analysis lies at the heart of this method. By recording and saving all of the I/Q data, it is possible to determine an analysis range in terms of the frequency, measurement bandwidth and recording time. The results can be displayed in graphical format, making the analysis process more efficient and providing a clearer presentation. The size of this range determines how many chirps are subsequently measured, and the chirp rate deviations relative to an ideal chirp are presented in a result table. The maximum measurement time decreases if a larger measurement bandwidth is selected. In addition, a timing window can be defined in order to neglect transients that occur during the measurement. An ideal chirp of this sort is determined by measuring the average chirp rate and the power. Analysis of the radar signals begins during the measurement process, since the I/Q data is recorded asynchronously and evaluated. Especially when working with signals with large bandwidths or in case of long measurement times, the duration of the analysis can be significantly reduced in this manner. Various choices are available for displaying the measurement results (e.g. RF spectrum, amplitude/frequency/phase modulation vs. time), and simultaneous display can be enabled. The spectrum analyzer can display the entire data memory, a userdefined interval or individual chirps. FM linearity For characterization of FM chirps, the FM linearity is very important, since it influences the accuracy of the object parameters. This can be displayed especially well using the spectrogram mode, which depicts how the signal’s spectrum fluctuates vs. time. Along with the frequency (x axis) and time (y axis), the Fig. 2 Speed and distance can be determined within a single measurement cycle using FM chirp sequences. 38 Electronic Engineering Times Europe October 2014 www.electronics-eetimes.com


EETE OCT 2014
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