Pedestrian Imaging Using UWB Doppler Radar Interferometry

Saho, Kenshi; Sakamoto, Takuya; Sato, Toru

doi:10.1587/transcom.e96.b.613

Cited by 21 publications

(37 citation statements)

References 23 publications

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“…For instance, in the tracking of a target moving with a constant jerk, bias error occurs. When vok=JT 2 /2 (J is the jerk), the steady-state bias error for the smoothed velocity is calculated using (8), (9), (11), and (12) as:…”

Section: Discussion For Parameter γmentioning

confidence: 99%

“…Position and radial velocity are measured at each interferometer using the imaging method described in [8]. The transmitted signal is the raised-cosine pulse Wrc(t) with a bandwidth of B and a center frequency of f0.…”

Section: System Model and Measurement With Doppler Radar Interferometersmentioning

confidence: 99%

“…Moreover, the interferometer measures the direction-of-arrival using the range difference between the two antennas δRk, which is determined by φk = Sin -1 (δRk/d). The details of the estimation methods for τk, fdk, and δRk are explained in [8]. The radar using these methods is called the Doppler radar interferometer.…”

Section: System Model and Measurement With Doppler Radar Interferometersmentioning

confidence: 99%

“…In [8], we achieved imaging of human outlines using the superposition of the orbits of scatterers estimated using a single Doppler radar interferometer. The velocity of the scatterer can be estimated by the time-derivative operation.…”

Section: Imaging With Single Doppler Radar Interferometermentioning

confidence: 99%

“…However, their resolution is insufficient and/or excessive computational resources and relatively large calculation times are required for these applications. To realize the coexistence of rapid/simple calculation and accuracy, we proposed a method to estimate an orbit of scatterers with a Doppler radar interferometer [8]. This method achieved real-time imaging of the orbit of a person walking using three fixed antennas and Doppler effect-based target separation and positioning.…”

Section: Introductionmentioning

confidence: 99%

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Velocity/Shape Estimation Algorithm Using Tracking Filter and Data Fusion of Dual Doppler Radar Interferometers

Saho¹,

Masugi²

2015

IJCEE

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An algorithm is proposed for estimating the shape and velocity of a moving target using dual Doppler radars. The proposed algorithm estimates a target velocity and orbit with a fusion of parameters measured by the dual Doppler radar interferometers and the α-β-γ tracking filtering. The accurate shape is then estimated by motion compensation using the estimated velocities. Numerical simulations verify that the proposed algorithm achieves accurate and real-time velocity/shape estimation. The root-mean-square error for velocity estimation is 1.20 cm/s and for shape estimation is 0.317 mm, which corresponds to 1/237 of the nominal resolution determined by the radar bandwidth.

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Section: Discussion For Parameter γmentioning

confidence: 99%

Section: System Model and Measurement With Doppler Radar Interferometersmentioning

confidence: 99%

Section: System Model and Measurement With Doppler Radar Interferometersmentioning

confidence: 99%

Section: Imaging With Single Doppler Radar Interferometermentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Velocity/Shape Estimation Algorithm Using Tracking Filter and Data Fusion of Dual Doppler Radar Interferometers

Saho¹,

Masugi²

2015

IJCEE

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Ultra‐wideband radar‐based accurate motion measuring: human body landmark detection and tracking with biomechanical constraints

Dai¹,

Zhou²,

Zhang³

et al. 2015

IET Radar, Sonar & Navigation

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The authors propose and investigate a methodology for accurate human motion measuring by detecting and tracking human body landmarks using ultra-wideband (UWB) radars. The proposed method can estimate the markers' positions and velocities in a two-dimensional space based on range measurements from a single radar given a prior information about the markers' initial states. The detection of multiple human body landmarks is achieved by moving target indication and a new out-of-band constant false alarm rate detection, and the multiple landmark tracking is accomplished by a novel iterative convex optimisation-based approach with considerations of biomechanical constraints. The data association technique is then applied to validate and relate the detection results to target landmarks for generating range measurements, which are used for a convex optimisation-based sequential estimation algorithm to estimate the accurate marker locations. It is noted that the proposed optimisation-based sequential estimation is able to incorporate biomechanical constraints. In the field experiments, two radio frequency reflectors are attached to the wrist and the elbow of one human arm. It is demonstrated that detection and tracking of the moving trajectories of two markers are successfully achieved, and thus, the human arm motion is accurately measured using one UWB radar.

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