In computer vision, optical camera is often used as the eyes of computer. If we replace camera with synthetic aperture radar (SAR), we will then enter a microwave vision of the world. This paper gives a comparison of SAR imaging and camera imaging from the viewpoint of epipolar geometry. The imaging model and epipolar geometry of the two sensors are analyzed in detail. Their difference is illustrated, and their unification is particularly demonstrated. We hope these may benefit researchers in field of computer vision or SAR image processing to construct a computer SAR vision, which is dedicated to compensate and improve human vision by electromagnetically perceiving and understanding the images.
Huynen decomposition prefers the world of basic symmetry and regularity (SR) in which we live. However, this preference restricts its applicability to ideal SR scatterer only. As for the complex non-symmetric (NS) and irregular (IR) scatterers such as forest and building, Huynen decomposition fails to analyze their scattering. The canonical Huynen dichotomy is devised to extend Huynen decomposition to the preferences for IR and NS. From the physical realizability conditions of polarimetric scattering description, two other dichotomies of polarimetric radar target are developed, which prefer scattering IR, and NS, respectively, and provide two competent supplements to Huynen decomposition. The canonical Huynen dichotomy is the combination of the two dichotomies and Huynen decomposition. In virtue of an
Adaptive selection, the canonical Huynen dichotomy is used in target extraction, and the experiments on AIRSAR San Francisco data demonstrate its high efficiency and excellent discrimination of radar targets.
In recent years, multi-input and multi-output (MIMO) radar has attracted much attention of many researchers and institutions. MIMO radar transmits multiple signals, and receives the backscattered signals reflected from the targets. In contrast with conventional phased array radar and SAR system, MIMO radar system has significant potential advantages for achieving higher system SNR, more accurate parameter estimation, or high resolution of radar image. In this paper, we propose a new MIMO SAR system based on Alamouti space-time coding scheme and orthogonal frequency division multiplexing linearly frequency modulated (OFDM-LFM) for obtaining higher system signal-to-noise ratio (SNR) and better range resolution of SAR image.
Noise radar has been applied in many fields since it was proposed more than 50 years ago. However, it has not been applied to interferometric SAR imaging yet as far as we know. This paper introduces our recent work on interferometric noise radar. An interferometric SAR system was developed which can transmit both chirp signal and chaotic noise signal (CNS) at multiple carrier frequencies. An airborne experiment with this system by transmitting both signals was carried out, and the data were processed to show the capability of interferometric SAR imaging with CNS. The results shows that although the interferometric phase quality of CNS is degraded due to the signal to noise ratio (SNR) is lower compared with that of chirp signal, we still can get satisfied DEM after multi-looking processing. Another work of this paper is to apply compressed sensing (CS) theory to the interferometric SAR imaging with CNS. The CS theory states that if a signal is sparse, then it can be accurately reconstructed with much less sampled data than that regularly required according to Nyquist Sampling Theory. To form a structured random matrix, if the transmitted signal is of fixed waveform, then random subsampling is needed. However, if the transmitted signal is of random waveform, then only uniform subsampling is needed. This is another advantage of noise signal. Both the interferometric phase images and the DEMs by regular method and by CS method are processed with results compared. It is shown that the degradation of interferometric phases due to subsampling is larger than that of amplitude image.
We propose to apply the compressive sensing technique to the design of satellite radar altimeter for increasing the sampling time window (STW) while keeping the same data rate so as to enhance the tracking robustness of an altimeter. A satellite radar altimeter can measure the range between the satellite platform where it is aboard and the averaged sea surface with centimeter level accuracy. The rising slope of the received waveform by altimeter contains important information about the sea surface, e.g. the larger the slope of the waveform, means the smoother the sea surface. Besides, the half-power point of the slope refers to the range information. For satellite altimeter, due to the rising slope just occupies fewer range bins compared with the whole range bins illuminated by the long pulse signal, i.e. the signal is sparse in this sense, thus compressive sensing technique is applicable. Altimeter echoes are simulated and the waveforms are constructed by using the traditional method as well as by compressive sensing (CS) method, they are very well agreed with each other. The advantage of using CS is that we can increase the sampling time window without increasing the data, thus the tracking capability can be enhanced without sacrificing the resolution.
KEYWORDS: Velocity measurements, Radar imaging, Radar, Signal to noise ratio, Motion measurement, Detection and tracking algorithms, Monte Carlo methods, Signal processing, Multiple scattering, Imaging systems
Stepped-chirp signal (SCS) is widely used by wideband high-resolution radars; however, its bandwidth synthesizing suffers from motion-induced phase errors resulting from the radial velocity of the target, especially for high-speed targets. So motion compensation is very crucial in signal processing for this kind of radar using SCS. Based on the cross-correlation inner frame method for velocity measurement of a single-scattering-center target, the multiple cross-correlation method (MCCM) is proposed for measuring the velocity of a complex target with multiple scattering centers (MSC), which is called SCS-MCCM. By this algorithm, not only the radial velocity, but also the real velocity of a target can be measured under the assumption that it is straight moving. After obtaining the velocity, motion compensation is conducted so as to realize high-resolution imaging. Theoretical analysis and simulations show that the proposed method is feasible and effective for an MSC target.
An investigation to the appropriate feature for SAR image registration is conducted. The commonly-used features such
as tie points, Harris corner, the scale invariant feature transform (SIFT), and the speeded up robust feature (SURF) are
comprehensively evaluated in terms of several criteria such as the geometrical invariance of feature, the extraction speed,
the localization accuracy, the geometrical invariance of descriptor, the matching speed, the robustness to decorrelation,
and the flexibility to image speckling. It is shown that SURF outperforms others. It is particularly indicated that SURF
has good flexibility to image speckling because the Fast-Hessian detector of SURF has a potential relation with the
refined Lee filter. It is recommended to perform SURF on the oversampled image with unaltered sampling step so as to
improve the subpixel registration accuracy and speckle immunity. Thus SURF is more appropriate and competent for
general SAR image registration.
This paper is dedicated to investigate the appropriate parameter retrieval algorithm for feature-based synthetic aperture
radar (SAR) image registration. The widely-used random sample consensus (RANSAC) is observed to be instable for its
inappropriate estimation strategy and loss function for SAR images. In order to enable a stable and robust registration for
SAR, an extended fast least trimmed squares (EF-LTS) is proposed which conducts the registration by least squares
fitting at least half of the correspondences to minimize the squared polynomial residuals instead of fitting the minimal
sampling set to maximize the cardinality of the consensus set as RANSAC. Experiment on interferometric SAR image
pair demonstrates that the proposed algorithm behaves very stably and the obtained registration is averagely better than
that by RANSAC in terms of cross-correlation and spectral SNR. By this algorithm, a stable estimation for any kind of
2D polynomial warp model with high robustness and accuracy can be efficiently achieved. Thus EF-LTS is more
appropriate for SAR image registration.
The experimental work on testing the wide-band transmitters and receivers developed for Ka-band and Ku-band radar
systems, as well as the signal processing algorithms were introduced. A city light-railway train was selected as the
imaged target. The wide-band transmitters and receivers were designed based on the stepped-frequency chirp signal
(SFCS) with 2GHz bandwidth synthesized. The Super-SVA technique was used to deal with the case of transmitting
SFCS with band gaps between subchirps for purpose of achieving the same bandwidth using as less as possible subpulses.
Both Ka-band and Ku-band high-resolution radar images were obtained, which show that Ka-band images are much
clear than that of Ku-band as we expect. There are two reasons to explaining this, one reason is due to the
electromagnetic scattering of train itself are different for Ka-band and Ku-band frequencies, and the other reason is due
to the interactions, i.e. multi-reflection or multi-scattering between the train and the side metal fences or the lamp post
This paper introduces a simple method to obtain a much higher resolution than the designed resolution in both azimuthal
and rang directions for SAR by synthesizing the data taken by repeat passes without increasing any complexity in SAR
hardware and satellite platform. The basic idea of the method is to firstly establish the equivalence between the signal
models of repeat pass SAR signals in both azithumal and range directions and the signal model of stepped frequency
chirp signals (SFCSs) when some conditions are presumed, i.e. for range direction, interferometric condition is required
and for azimuthal direction, a small squint angle increase between repeat passes is required, and then using the already
proposed method for SFCSs compression to process the data of repeat passes. In the course of processing, each
observation in range direction or in azimuthal direction is treated as a subchirp in SFCSs. The major facts affecting the
final resolution one could get are investigated and found. They are the relative range measurement accuracy and the
absolute squint angle measurement accuracy between repeat passes. Detailed derivations and simulations are presented
to show the effectiveness of the method.
The concept of Delay/Doppler Radar Altimeter (DDA) was proposed by R.K Raney<sup></sup> to improve the spatial resolution in the along-track direction, for rougher surfaces more irregular than open oceans. DDA also has many new advantages when it is used for open oceans, such as stronger response, being less sensitive to off-nadir angle errors, and being more sensitive to significant wave height (SWH) than Conventional Radar Altimeters (CRA). These new features and advantages will be validated by simulations in this paper.
Echo tracking is always an important part in the design of radar altimeter, which is required in many ways. But above all, the essential requirement for the tracking is to avoid track losing, furthermore, the tracking precision and algorithm operation scale also are need to be optimized. So all the factors mentioned above have to be considered comprehensively. Till today, various tracking algorithms have been developed for different applications, but the common shortage of them is that they depend on some specific target modes strongly, which leads to poor adaptability to different targets and easily losing tracking. As to this problem, OCOG will be introduced in this paper, which is a good robust tracking algorithm and will be applied into a new type of satellite altimeter, tridimensional imaging radar altimeter, which will be applied in complex environments including sea, seaice and coast.
The design of the China Imaging ALTimeter (CIALT) and the flight experiment of its airborne model are presented in this paper. The system is aimed for providing observation measure for both oceanic applications and continental topographic mapping in the future. The motivation of this project is to develop a three dimensional imager fitted for small satellites with small volume, mass and power consumption. An experimental airborne model of the CIALT has been developed for verifying the design concept. The CIALT integrates three techniques together, i.e. the height measurement and tracking technique of traditional radar altimeter used for ocean applications, the synthetic aperture technique and the interferometric technique. A robust height tracker has been designed for meeting the requirements of both oceanic surfaces and continental surfaces (including surfaces of ice continent). The synthetic aperture technique is used for achieving a higher azimuthal resolution along the cross range direction compared with that of a traditional altimeter. The interferometric technique is used for retrieving the height information corresponding to each image pixel and for boresight angle correction of the antennas, which is crucial for accurate height measurement. The CIALT is different from other proposed imaging altimeters, such as SAR altimeter and scanning altimeter, in which no height tracker is involved. Some key technologies regarding the development of imaging altimeter are addressed, such as the antenna design, the transmitter, the receiver and the robust tracking algorithm.