Spatial filtering velocimeter using frequency shifting
by the method of rotating kernel
Xin He, Xingwu Long
⇑
, Xiaoming Nie, Jian Zhou
College of Optoelectronic Science and Engineering, National University of Defense Technology, Changsha 410073, China
article info
Article history:
Received 7 January 2015
Received in revised form 15 April 2015
Accepted 6 May 2015
Available online 14 May 2015
Keywords:
Spatial filtering velocimeter
Rotating kernel
Maximum measurable velocity
Standard uncertainty
Power spectrum
abstract
A new approach of frequency shifting by rotating kernel is proposed to improve the
performance of a spatial filtering velocimeter, used to provide accurate velocity informa-
tion for a vehicle self-contained navigation system. A linear CMOS image sensor was
employed both as a spatiotemporal differential spatial filter and as a photodetector. The
filtering operation was fully performed in FPGA and is realized by applying a rotating ker-
nel to the pixel values of the image. Theoretical analysis showed this method could double
the maximum measurable velocity. The power spectrum of the output signal was obtained
by fast Fourier transform (FFT), and was corrected by a frequency spectrum correction
algorithm, named energy centrobaric correction. This velocimeter was used to measure
the moving velocities of a conveyor belt. Experimental results verified the method’s ability
of reducing the output signal frequency and standard uncertainty of velocity measurement.
What is more, the undesired output introduced by frequency shifting to the power spec-
trum of the output signal was deeply investigated and a new method was proposed to
eliminate the undesired component in output signals. This velocimeter aims at providing
accurate velocity information for vehicle autonomous navigation system.
Ó 2015 Elsevier Ltd. All rights reserved.
1. Introduction
The demand for reliability of autonomous navigation
systems is increasingly high. The navigation system needs
to be fully autonomous and should be able to continuously
position with high accuracy. However, in vehicle autono-
mous navigation systems, the velocity information is pre-
sently provided by accelerometers, which have divergent
trends over time. Therefore, the idea of using a velocimeter
to measure the velocity for the vehicle autonomous navi-
gation system was put forward [1]. There are some meth-
ods of optical velocity measurement, such as laser Doppler
velocimetry, laser speckle velocimetry and spatial filtering
velocimetry. These methods have all been used to measure
the velocity of vehicles relative to ground surfaces [1–4].
Therefore, all of them have the potential for application
to vehicle autonomous navigation systems. However, the
first two methods using laser as the illumination cannot
satisfy the requirements of reliability at high ambient tem-
perature, long life of its light source and reasonable cost,
whereas the spatial filtering velocimeter can meet with
all the requirements above.
In spatial filtering velocimetry the spatial filtering
device is the most important element. There are roughly
four types of spatial filters being applied to the spatial fil-
tering velocimeter [5]: transmission grating type [6],
detector type [7,8], optical fiber type [9] and other special
grating type [10–12]. A detector type of spatial filtering
device, a linear image sensor, is used in our system. The
image sensor operates both as a spatial filter and as a pho-
todetector. However, the frame rate limits the maximum
detectable velocity, making the measurement range unable
to cover all the velocities of the vehicle. Although an
http://dx.doi.org/10.1016/j.measurement.2015.05.013
0263-2241/Ó 2015 Elsevier Ltd. All rights reserved.
⇑
Corresponding author.
E-mail address: xwlong110@sina.com (X. Long).
Measurement 73 (2015) 15–23
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