In this paper, a new method to suppress both barrage jamming and deceptive jamming is proposed based on spaceborne azimuth multichannel synthetic aperture radar (AMSAR). The relationship between signals received over arbitrary channel and reference channel is obtained by analyzing the signal models of the jammed AMSAR. Based on this relationship, a system of equations, whose solution contains SAR echo and all jamming signals, is established. In order to obtain high-precision solutions, the system noise has to be removed and accurate direction of arrival (DOA) estimation of jammers is required. For this purposes, a singular value decomposition (SVD) based method for noise reduction and a least square method for the two-dimensional locations of jammers are put forward. By solving the equations, SAR echoes can be recovered. Finally, several simulation experiments are provided to illustrate the effectiveness of the proposed method.
Notch filtering is a popular technique to remove radio-frequency interference (RFI), due to its ease of implementation. However, significant degradation in performance occurs when RFI exhibits characteristics of high nonstationarity. Motivated by this challenge, this paper proposes a method that can not only effectively remove nonstationary RFI but can also obtain a well-focused image. The time-frequency (TF) distribution is constructed by short-time Fourier transform (STFT) with a nonoverlapping window in each slow time. The points of TF distribution belonging to RFI can be detected through a threshold and removed. Having sorted the remaining TF points, only points with the highest value belonging to the target echoes are retained, whereas the other points are set to zero and cast as missing samples. The linear relationship between the STFT vector and the range profile in the fractional Fourier transform domain is then established. Using sparsity, the range profile can be reconstructed by solving a minimization problem without any distortion. Finally, a two-dimensional image is obtained by the fractional range-Doppler algorithm. The results of simulations and experiments showed the effectiveness of the proposed method.
In order to form a false scene in Synthetic Aperture Radar (SAR) image, deceptive jammer need to get the relevant SAR parameters. In these parameters, squint angle and beamwidth usally change and it will make the pre-generated jamming signal unuseful. For solving this problem, a strategy is proposed to transform the pre-generated jamming signals to counter SAR with arbitrary squint angle and beamwidth in real time. Firstly, the jamming effects under estimation errors of SAR’s squint angle and beam-width are analyzed. Using Graphics Processing Units (GPU), a parallel algorithm to generate jamming signals for varying squint angle and azimuth beam-width is proposed. Then, This paper describes a method that can implement the signal transformation between wide-beam condition and narrow-beam condition. Based on the generated signals, the jamming under arbitrary squint angle and beam-width can be realized in real time. The simulation results shows that this strategy is effective to jam SAR with varieties of squint angles and wide-beams.
Distortion compensation of High-resolution range profile plays an important role in ISAR imaging of high-speed space
target. Since the baseband echo of such target is a multi-component linear frequency modulated(LFM) signal with
identical chirp rates. Since the peaks of its ambiguity function lie on a set of parallel lines, whose slope is relative to the
chirp rate, an estimator based on the fractional autocorrelation is provided to estimate the target's radial velocity.
Furthermore, the particle swarm optimization(PSO) algorithm is also applied to speed up the progress of parameter
estimation,. Finally, the velocity compensation is accomplished with the estimated velocity. Simulations show that the
proposed method can compensate the range profile distortion of space target effectively.