This paper introduces a modified random sample consensus (M-RANSAC) and short-time fractional Fourier transform (STFRFT)-based algorithm for feature extraction of synthetic aperture radar (SAR) scattering centers. In this algorithm, the range migration curve (RMC) of a scattering center is formulated as a parametric model. By estimating these parameters, the backscattering envelope of scattering center, corresponding to the backscattering variation in synthetic aperture time, is extracted directly from a time-domain range-compressed signal. The estimated parameters can also reconstruct the geographical location and along-track velocity of scattering centers. Thus, even without knowing explicit knowledge of platform velocity and forming a SAR image, this algorithm is capable of realizing feature extraction. To estimate parameters scatter by scatter, M-RANSAC approach is proposed as an implementary method with iterative procedure. In the iterations, fitting precision indicator (FPI) works cooperatively with construction fitness coefficient (CFC) to determine the optimal parameters of different scattering centers. Adapting this method to more general cases, STFRFT is introduced to separate the overlapped trajectories of RMCs of scattering centers. The root mean squared errors (RMSEs) of parameter estimation are close to their Cramér-Rao lower bounds (CRLB). The effectiveness of feature extraction based on the devised algorithm is validated by both simulated and real SAR data.
Optimal waveform-based clutter suppression algorithm for recursive synthetic aperture radar imaging systems," Abstract. A computational method for suppressing clutter and generating clear microwave images of targets is proposed in this paper, which combines synthetic aperture radar (SAR) principles with recursive method and waveform design theory, and it is suitable for SAR for special applications. The nonlinear recursive model is introduced into the SAR operation principle, and the cubature Kalman filter algorithm is used to estimate target and clutter responses in each azimuth position based on their previous states, which are both assumed to be Gaussian distributions. NP criteria-based optimal waveforms are designed repeatedly as the sensor flies along its azimuth path and are used as the transmitting signals. A clutter suppression filter is then designed and added to suppress the clutter response while maintaining most of the target response. Thus, with fewer disturbances from the clutter response, we can generate the SAR image with traditional azimuth matched filters. Our simulations show that the clutter suppression filter significantly reduces the clutter response, and our algorithm greatly improves the SINR of the SAR image based on different clutter suppression filter parameters. As such, this algorithm may be preferable for special target imaging when prior information on the target is available. Downloaded From: http://remotesensing.spiedigitallibrary.org/ on 06/29/2016 Terms of Use: http://spiedigitallibrary.org/ss/TermsOfUse.aspxWaveform design, which has been investigated extensively, has recently become of great importance to many applications. The goal of this design is to learn about an object or environment by transmitting optimal waveforms while suppressing clutter and noise simultaneously. Early investigations on detection in the presence of clutter in space-time adaptive processing 1 and waveform design for clutter rejection 2,3 assumed that clutter returns were independent and Gaussian distributed. The problem of matching a known target response with signal-dependent interference and additive channel noise was first investigated in Ref. 4. Traditional waveforms, such as chirp signals, were found to have inferior signal-to-clutter plus noise ratio (SINR) performance for extended targets. Earlier studies on signal design for detection and identification include Refs. 5 , 6 Goodman summarized and demonstrated a framework to implement closedloop radar with adaptive waveforms in Refs. 7, 8. Kay modeled the received signal in the frequency domain and derived the optimal NP detector in Ref. 9, 10. Other works 11,12 considered a problem related to that of Ref. 9 under a peak-to-average power ratio (PAPR) constraint, in which the author considered the problem of knowledge-aided transmit signals and receiver filter designs for point-like targets in signal-dependent clutter. The study in Ref. 13 dealt with the joint design of transmitted sequences and receiver filters under similar constraints in case...
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.