China
Africa
Explore chapters and articles related to this topic
Analyzing Tropical Cyclones over India Using Precipitation Radar
Published in George P. Petropoulos, Tanvir Islam, Remote Sensing of Hydrometeorological Hazards, 2017
Devajyoti Dutta, A. Routray, Prashant K. Srivastava
The principle of Doppler weather radar is based on Doppler effect. Shift in frequency caused by moving sources of sound is directly proportional to speed of the source. Doppler radar compares the received signal with the frequency of the transmitted signal and measures the frequency shift, giving the speed of the target. For a radar with wavelength λ observing a target at range r, if radar signal is transmitted with initial phase of [φ0], then the phase of returned signal φt will be [φ0−4p r (t)/l]. If the target is moving with respect to the radar with a radial velocity vr, the phase of the signal varies, and we have: () dΦ(t)dt=ωd=2 πfd=−4πλdr(t)dt=−4πλvr
Fundamentals of Indoor Radar
Published in Moeness G. Amin, Radar for Indoor Monitoring, 2017
Aboulnasr Hassanien, Braham Himed
A pulse-Doppler radar is a radar system that is designed to simultaneously determine the range and velocity of a target, that is, it combines the features and benefits of pulse and CW radars. The target range is determined using pulse-timing techniques via measuring the time required for the transmitted pulse(s) to hit the target and for the reflected wave to arrive at the radar receiver. At the same time, the Doppler effect of the returned signal is used to determine the velocity of the target. Another essential feature of pulse- Doppler radar is its ability to detect small targets observed in the background of strong clutter. Although pulse-Doppler radar was introduced during World War II, it was first widely used on fighter aircrafts starting in the 1960s. Since then, pulse-Doppler radar has been continuously developed, and sophisticated pulse-Doppler systems have been built for both military and civilian applications. In military applications, pulse-Doppler radars permit reducing the transmitted power while achieving acceptable performance. Among the civilian applications, pulse-Doppler radar systems have successfully been employed in meteorology, remote sensing and mapping, air traffic control, as well as in conventional surveillance applications. During the last decade, pulse-Doppler radar has received much attention in automotive and health-care applications. In particular, it has been successfully applied for elderly assisted living, fall risk assessment, and fall detection (Mercuri et al., 2013; Su et al., 2015; Jokanovic et al., 2015; Amin et al., 2016; Diraco et al., 2016; Erol and Amin, 2016b; also see Chapter 6).
Applications of Sensors to Physical Measurements
Published in Robert B. Northrop, Introduction to Instrumentation and Measurements, 2018
In this section, we will examine a class of closed-loop measurement system that gives simultaneous analog output voltages proportional to target range and velocity along the range vector. Recall that conventional radar works by measuring the time it takes a transmitted pulse to return to the receiver after being reflected from the target. Doppler radar measures the frequency shift of the reflected pulse and computes the target velocity from this information. Sonar works in essentially the same manner. The laser velocity and range finder (LAVERA) phase-lock method adjusts the transmitted frequency under closed-loop control in order to keep the phase lag constant between received and transmitted waves.
An adaptive filtering algorithm in pulse-Doppler radar for counteracting range-velocity jamming
Published in International Journal of Electronics, 2022
Ahmed Abdalla, Mohammed Ramadan, Yongjian Liao, Shijie Zhou
Primarily, Doppler radar is employed for the detection of moving targets whose echo region is much smaller than the relatively stationary clutter return. Moving targets are discriminated from noise, clutter, and jamming on a frequency basis by exploiting the Doppler phenomenon. Conventionally, the pulse-Doppler radar repeats the same waveform to permit efficient pulse compression and Doppler processing technique to be utilised.
High-resolution simulation-based analysis of leading vehicle acceleration profiles at signalized intersections for emission modeling
Published in International Journal of Sustainable Transportation, 2021
Sicong Zhu, Inhi Kim, Keechoo Choi
Currently, a number of researches have been undertaken on leading vehicle (vehicle platoon leader) acceleration behavior at intersections. The common assumptions are constant acceleration and decreasing acceleration (Zhang et al., 2013). Wang et al. (Wang et al., 2004) have assumed that drivers normally accelerate with a polynomial decreasing relationship with speed. Long (Long, 2000) has concluded that linearly decreasing acceleration rates better represent both maximum vehicle acceleration capabilities and actual motorist behavior. To address the issue, the initial and primary challenge is data collection: High-resolution and accurately positioned vehicle trajectory datasets are difficult to obtain in practice. The trajectory datasets are commonly collected by three techniques, namely vehicle-mounted GPS, Doppler radar, and feature–capture camera (Bogdanović et al., 2013; Gordon, 2012). The data accuracy of the GPS is subject to surrounding environments (Boonsiripant et al., 2010), which downgrade the reliability of the leading vehicle acceleration data. Moreover, the update rate of GPS set is limited (Pham & Drieberg, 2013). The trajectory data captured by cameras have been criticized for the problems of positioning accuracy and integrity (Punzo et al., 2011). Moreover, the calibration of camera is another issue for the data reliability (Zhang, 2000). The Doppler radar has two variants, namely continuous wave (CW) and frequency-modulated continuous wave (FMCW). A CW Doppler radar senses the frequency shift in terms of Hertz between the transmitted signal and the reflected signal (Kim & Coifman, 2017). This frequency shift is used to detect vehicle presence and calculate speed based on the Doppler principle. CW Doppler radar units cannot detect stationary objects. Therefore, it is especially difficult to track vehicle trajectories at signalized intersections as stopped vehicles will disappear from the radar screen. And it is very difficult to identify multiple targets (Bilik et al., 2006; Roy et al., 2011). When vehicles are stopped at an intersection, the radar system may mistake queued consecutive passenger cars for a long truck. A FMCW radar unit transmits an electromagnetic wave, the frequency of which is continuously being adjusted with time. Because of this modulated frequency, it is possible to determine the range to the vehicle. Consecutive range readings are used to determine the vehicle speed. A FMCW radar unit is able to detect stopped vehicles. The latter method has excellent detection capability for mobile objects, such as cyclists and pedestrians, down to 5 km/h (Jeng et al., 2014). However, both categories of the Doppler radars are not suitable for trajectory data collection at intersection.