Radar imaging consists of data pre-processing, calibration
and imaging procedures. The pre-processing removes antenna
coupling along with unwanted reflections by background
subtraction and suppresses noise by a 10-18 GHz band-pass
finite impulse response filter. It also includes deconvolution of
the system impulse response out of the pre-processed data in
order to compress the received pulse that improves down-range
resolution and, finally, the sharpness of the focused image. The
calibration makes the time scale of the acquired radar signal
corresponding to its actual travel time to target and back. A
small metal sphere placed at a given distance is used to
calibrate the system. The estimated time shift between the
actual and measured travel times is applied to all the data
measured afterwards.
The imaging technique is based on Kirchhoff migration that
has been widely used in seismology and recently applied to
UWB radar imaging [7, 8]. It accounts for the wave front of the
scattered electromagnetic field, which results in a more
accurate target reconstruction than ray approximation. For
multi-static radar configuration Kirchhoff migration can be
expressed as follows
() ( ) 12 12 0
1
,coscos , t
RR u t u t dxdy
t
φφνν=
∂+′ =+ + ∂
rr(1)
where 1 Rand
2 Rstand for distances Tx – target and target –
Rx respectively, 1 φand
2 φ indicate the respective aspect
angles, νstands for the propagation velocity. Note that
differentiation of the signal in time increases noise but this
effect is normally compensated by the spatial integration. The
cosines in the formula suppress signals from other aspect
angles which reduces the sidelobes. Due to its linear
formulation, Kirchhoff migration can be implemented
reasonably fast in practice.
Radar imaging consists of data pre-processing, calibration and imaging procedures. The pre-processing removes antenna coupling along with unwanted reflections by background subtraction and suppresses noise by a 10-18 GHz band-pass finite impulse response filter. It also includes deconvolution of the system impulse response out of the pre-processed data in order to compress the received pulse that improves down-range resolution and, finally, the sharpness of the focused image. The calibration makes the time scale of the acquired radar signal corresponding to its actual travel time to target and back. A small metal sphere placed at a given distance is used to calibrate the system. The estimated time shift between the actual and measured travel times is applied to all the data measured afterwards. The imaging technique is based on Kirchhoff migration that has been widely used in seismology and recently applied to UWB radar imaging [7, 8]. It accounts for the wave front of the scattered electromagnetic field, which results in a more accurate target reconstruction than ray approximation. For multi-static radar configuration Kirchhoff migration can be expressed as follows () ( ) 12 12 01,coscos , tRR u t u t dxdytφφνν=∂+′ =+ + ∂ rr(1) where 1 Rand 2 Rstand for distances Tx – target and target – Rx respectively, 1 φand 2 φ indicate the respective aspect angles, νstands for the propagation velocity. Note that differentiation of the signal in time increases noise but this effect is normally compensated by the spatial integration. The cosines in the formula suppress signals from other aspect angles which reduces the sidelobes. Due to its linear formulation, Kirchhoff migration can be implemented reasonably fast in practice.
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