For the current smart high-speed scene, the millimeter-wave radar needs to give the lane number of the vehicle while outputting the lane-level target track information. Since the millimeter-wave radar cannot identify the lane line information, it is difficult to achieve the lane estimation without the help of other sensors. This paper proposes a method to quickly estimate the lane numbers of vehicles in different high-speed scenarios with the help of high-precision maps. First, it unifies the map and vehicle track coordinate system, converts the point set of lane line in WGS-84 format to the Cartesian coordinate system with the radar as the origin after coordinate transformation. Then, through Lagrange interpolation, the X value corresponding to the Y value of the vehicle on the left and right side of the lane line is obtained. Finally, the lane to which the vehicle belongs is estimated by the ratio method. The actual measurement results show that the method can quickly and accurately estimate the lane number of the vehicle in various high-speed scenarios without the help of other sensors.
There are a lot of shortcomings with traditional optical adjustment in interferometry, such as low accuracy, time-consuming, labor-intensive, uncontrollability, and bad repetitiveness, so we treat the problem by using wireless remote control system. Comparing to the traditional method, the effect of vibration and air turbulence will be avoided. In addition the system has some peculiarities of low cost, high reliability and easy operation etc. Furthermore, the switching between two charge coupled devices (CCDs) can be easily achieved with this wireless remote control system, which is used to collect different images. The wireless transmission is achieved by using Radio Frequency (RF) module and programming the controller, pulse width modulation (PWM) of direct current (DC) motor, real-time switching of relay and high-accuracy displacement control of FAULHABER motor are available. The results of verification test show that the control system has good stability with less than 5% packet loss rate, high control accuracy and millisecond response speed.
The joint transform correlator was an effective system for the target detection and recognition, major character was that
the reference template and the target were simultaneous processed; Fourier transform was operated by Fourier transform
lens with the speed of light; the joint transform power spectrum was obtained through the first Fourier transform, then
got the correlation peaks through the second Fourier transform.
The power spectrum of the joint transform correlator was recorded by the Charge Coupled Device (CCD) matrix
camera. The contrast of the power spectrum was relatively lower, so some important information, such as the Young's
interference fringes, were displayed very fuzzy, even couldn't see in some images, the output correlation peaks were
seriously affected. For enhancing the power spectrum's contrast, the power spectrum may be filtered with the high-boost
filtering. By filtering, the contrast of the Young's interference fringes was greatly improved and displayed relatively clear,
so the contrast of the correlation peaks were greatly enhanced, the recognition ratio of the target detection and
recognition by the joint transform correlator was increased. As the experiment examples, the target recognition of a car
and a warship in cluttered scenes were presented. The experiments showed that the contrast of the Young's interference
fringes was improved after the joint transform power spectrum was processed by the high-boost filtering. At the same
time, the output correlation peaks were obviously enhanced too. So the high-boost filtering was very effective method for
filtering in the joint transform power spectrum.
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