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The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Vol. XXXVII. Part Bl. Beijing 2008 
(digital elevation model) topography. Note that, in monostatic 
radar, the scene topography is not considered in the focusing 
algorithms because the measured range delay is directly related 
with the double target distance and the observed range 
curvature. Therefore, some new imaging algorithms should be 
developed for near-space passive remote sensing. 
5,3 Motion Compensation 
For many creative applications of near-space passive radar, 
strict relative position or altitude is required. In this paper, we 
suppose the near-space platform is stationary. However, as a 
matter of fact, problems arise due to the presence of 
atmospheric turbulence, which introduce aircraft trajectory 
deviations from the nöminal position, as well as altitude (roll, 
pitch, and yaw angles). For current radar systems, the motion 
compensation is usually achieved with GPS and INU (Inertial 
Navigation Units). However, for near-space passive remote 
sensing the motion measurement facilities may be not reachable, 
the conventional motion sensors based motion compensation 
techniques may be not applicable any longer, so some new 
efficient motion compensation algorithms must be developed. 
To reach this aim, we can use the transponder proposed by 
(Weiß, 2002), as shown in Fig. 6, to extract the motion 
compensation information. 
Figure 6: Transponder based motion compensation. 
This transponder consists of a low-noise amplifier followed by 
a bandpass filter. A voltage controlled attenuator (VCA) is used 
to modulate the radar signal in a manner that the retransmitted 
signal will show two additional Doppler frequencies. Thereafter 
the signal will be amplified to an appropriate level and 
retransmitted towards the near-space receiver. This transponder 
can be seen as an amplitude modulator, that is 
echo of the transponder without the amplitude modulation, 
respectively. After applying a Fourier transform to Eq. (20), we 
have 
S,(f) = S,(f) + aS m (f) 
ß ß (21) 
The upper and lower side bands of this signal can be acquired 
using appropriate filters. Notice that, the filter bandwidth has to 
be chosen according to the signal bandwidth of s m (t) and the 
frequency distance between the clutter and the modulation 
frequency f m . If let 
The starting phase cp m can be calculated as 
s a {f+f m )-s;{f-f m )=ße i ^ 
(22) 
(23) 
A (/) = [a + ßcos(2xfJ + (p m )\ s 0 (/) 
(19) 
modulo n . Using this starting phase, the transponder signal 
can be calculated by 
, x \S(/ + f m )e J,p " +S h (f-f y v ” 1 
S m (f) = ^21—ixl b Xi—¿XL i (24) 
ß 
Thereafter, S m (f) can be transformed back into its time 
representation s m (t) using an inverse Fourier transform. 
Evaluation of the phase of s m (t) leads to a motion 
compensation solution. Note that another possible motion 
compensation solution is raw data based autofocus algorithms. 
We plan to carry out further investigation on this topic during 
subsequent work. 
with f m is the modulation frequency of transponder, tp m the 
starting phase and s 0 (t) the GNSS transmitted signal. We can 
notice that, the retransmitted signal will show the original 
GNSS signal and two additional Doppler frequencies, one 
positive and one negative shifted, allowing to extract the 
motion compensation information without clutter interferences. 
The corresponding near-space sensor received signal can be 
represented by 
s r (/) = Ä ä (f) + [a + ß cos(2;r f m t + (20) 
where s s (t) and s m (t) denote the un-modulated part and the 
6. CONCLUSION 
Near-space can provide many functions more responsively and 
more persistently than satellite and airplane for several reasons. 
First, it can support uniquely effective and economical 
operations. Second, it enables a new class of especially useful 
intelligence data. And finally, it provides a crucial corridor for 
prompt global strike. Inspired by recent advances in near-space 
technology, this paper presented the system concept of near 
space passive remote sensing for homeland security 
applications. The novelty of this paper is the application of 
near-space remote sensing to homeland monitoring and to 
related applications. When one understands that it is effects 
instead of the platform from which the effects are delivered, 
near-space makes much sense for homeland security 
applications. Note that there are many other possible 
applications, e.g., disaster monitoring. Recently the frequency