**2. Radar sensor and measurements**

Several proposals for pedestrian recognition schemes have been described, which are based on video cameras and computer vision systems [7], [8]. But automotive radar sensors in the

©2013 Heuel and Rohling, licensee InTech. This is an open access chapter distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0),which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. ©2013 Heuel and Rohling, licensee InTech. This is a paper distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

2 Will-be-set-by-IN-TECH 242 Ultra-Wideband Radio Technologies for Communications, Localization and Sensor Applications Pedestrian Recognition Based on 24 GHz Radar Sensors <sup>3</sup>

24 and 77 GHz band are also strong candidates for automotive safety systems. Compared with vision systems, they have some additional important advantages of robustness in all weather conditions, simultaneous target range and radial velocity measurement and a high update rate. These properties are especially important for pedestrian recognition, as the object classification should be available immediately and at any time.

high resolution and accuracy. The echo signal of the stepwise and intertwined waveform is downconverted by the corresponding instantaneous transmit frequency into baseband and sampled at the end of each short frequency step. This time discrete signal is Fourier transformed separately for the two intertwined signals to measure the beat frequency *f*<sup>B</sup>

which is simultaneously influenced by the target range *R* and radial velocity *v*r.

**Figure 2.** MFSK waveform principle with two intertwined transmit signals.

*fB* <sup>=</sup> <sup>−</sup>2*v*<sup>r</sup>

ΔΦ <sup>=</sup> <sup>−</sup> <sup>2</sup>*<sup>π</sup>*

described in Equation (3) and (4), respectively.

*<sup>λ</sup>* <sup>−</sup> <sup>2</sup>*<sup>R</sup>* · *<sup>f</sup>*sweep

In any case, a single target will be measured and will be detected on the same spectral line at position *f*<sup>B</sup> for the two intertwined signals. Therefore, after the detection procedure the phase difference ΔΦ between the two complex-valued signals on the spectral line *f*<sup>B</sup> will be calculated. The step frequency *f*step between the intertwined transmit signals determines the unambiguous phase measurement ΔΦ in the interval [−*π*;*π*). This phase difference ΔΦ again

The target range *R* and radial velocity *v*r can be determined by solving the linear equation described in Equation (1) and (2) in an unambiguous way. In this case, ghost targets are completely avoided since this waveform and signal processing combines the benefits of linear FMCW and FSK technology. The system design and the sensor parameters can be determined like in a linear FMCW radar system. The range and velocity resolution Δ*R* and Δ*v* are determined by the bandwidth *f*sweep of the radar sensor and the chirp duration *T*CPI as

is influenced by the target range *R* and radial velocity *v*r described in Equation (2).

*f*sample · 2*v*r

*<sup>c</sup>* · <sup>1</sup>

*<sup>λ</sup>* <sup>−</sup> <sup>4</sup>*π<sup>R</sup>* · *<sup>f</sup>*step

*<sup>c</sup>* (2)

Pedestrian Recognition Based on 24 GHz Radar Sensors 243

*T*CPI

(1)

**Figure 1.** Daily traffic situation in an urban area with an oncoming vehicle and pedestrians walking on the sidewalk.

This chapter presents the modulation scheme of an automotive radar sensor and explains the features of pedestrians and vehicles by which a robust classification is possible in an urban area from a moving vehicle with a mounted 24 GHz radar sensor, see Figure 1.
