Aiming at the problem that the target signal is difficult to be detected under the strong ground clutter environment, this paper proposes a clutter suppression algorithm based on the combination of singular value decomposition and Mallat fast wavelet algorithm.The method firstly performs singular value decomposition on the echo data matrix, and realizes the initial separation of target and clutter through the threshold processing of singular value. After that, wavelet decomposition is performed on the echo data to find out the target location, and the discard method is used to select the appropriate wavelet decomposition layer for target reconstruction, which ensures that the loss of target information is minimized while suppressing the clutter. Through experimental verification of the measured data, the method has significant effect on target extraction under low SCR conditions, and it can realize the separation of target and clutter in the absence of target a priori position information. The output SCR of the method is also improved compared with the traditional wavelet processing method.

In this paper, we propose an adaptive constant false alarm detection method based on background Discrimination (BBD-CFAR) to address the issues of degraded performance in detecting clutter edges and multi-neighbor targets. The proposed method utilizes non-uniform clutter estimation to maintain a constant false alarm rate and introduces mean ratio and clutter power interval to discriminate the detection background. We use an iterative approach to improve the detection probability of multi-neighbor target backgrounds. The BBD-CFAR method is applied to clutter backgrounds with different powers and multi-neighbor target backgrounds. Its ability to suppress neighboring target interference and improve detection performance at clutter edges is evaluated through Monte Carlo simulations. The experimental results demonstrate that the proposed BBD-CFAR method has superior detection performance in multi-neighbor target backgrounds and clutter edges.

When radar uses linear frequency modulated(LFM) stepped-frequency waveform (SFW) to image moving targets, because of its large time-bandwidth product, the motion of the target will produce serious motion phase error, causing energy diffusion, and may even be drowned in noise, unable to detect the target. Usually, for moving targets, it is necessary to estimate the velocity along with detecting it, and then synthesize a high-resolution range profile(HRRP) after migrating and phase compensation of the echoes to eliminate the effect of target motion. On this basis, a new motion parameter estimation method, based on Lv's distribution (LVD), is proposed based on the echo phase characteristics of the LFM stepped-frequency signal velocity estimation method. The effectiveness of this method has been verified through simulation. It can accumulate echo energy well without blind sidelobes and false targets and is still suitable for multi-target scenarios. While accurately estimating target velocity, it still has good detection and velocity estimation performance in low SNR situations.

Angular scintillation error is the main error source of millimeter-wave guidance heads seeking guidance. The monopulse angular algorithm based on high-resolution radar can effectively improve the angular scintillation phenomenon. Most of the existing studies are based on the idea of amplitude weighting, using the amplitude information of the distance unit for weighting. In this paper, based on the Minimum Mean Square Error (MMSE) criterion, combined with the High Range Resolution Profile (HRRP) goniometric algorithm, an adaptive weighting method is proposed to fuse and analyze the position and amplitude information [1], and finally, an Extended Kalman Filter (EKF) is used for angle smoothing. Simulation experiments show that the algorithm has a good suppression effect on angular flicker.

In this paper, a new method for solving target range ambiguity in radar signal processing based on subarray FDA-MIMO is proposed. At the same time, The optimal frequency shift selection of the transmit array is also analyzed. Compared to the FDA-MIMO radar with linear frequency shift, the new method is able to exclude the effect of ambiguous range peaks in FDA detecion and has a better result in supressing noise. The new method also extend the maximum unambiguous range, so it is more advantageous in the detection of multiple targets.

In this paper, an AMF detection method based on frequency diverse array(FDA) is proposed. Since the beampattren of FDA has range resolution capability, comparing to phase radar AMF detection, FDA-based radar AMF detection method can give both angular information and range information of the target. The new method also has better detection capability than GLRT method and CFAR method in case of high SNR. Frequency diverse array, AMF detection, FDA-MIMO.

Ground moving target indication (GMTI) has been extensively applied in modern warfare. In this letter, a novel deceptive jamming technique for countering multichannel synthetic aperture radar (SAR)-GMTI is presented, which is implemented with the frequency diverse array (FDA). Different from the phased array (PA), FDA modulates the transmitting signal with multiple frequencies across its array elements, which, consequently, enables range-dimension false target deception for SAR imaging. Furthermore, to achieve effective deception for the GMTI, micromotion modulation is adopted to simulate dynamic features of the moving targets. Mathematical derivation and simulation results show that the proposed technique can efficiently produce massive false targets in both the range and azimuth dimensions.

This paper introduces the hardware design and implementation of Omega-K imaging algorithm. Based on the analysis of Omega-K algorithm theoretical derivation, we plan to use pipeline structure and soft IP multiplexed method to speed up the imaging speed and achieve the purpose of real-time imaging. By evaluating the hardware resources and system running time needed in the design, we can realize the real-time imaging. So, we select the appropriate hardware platform to implement. Finally, we verify the design scheme by using the actual radar echo data of 13 seconds. The experimental results show that the peak signal- to- noise ratio of the imaging results by the hardware platform is 39.23dB, and the imaging time of the hardware platform is 9.38 seconds. This shows that the imaging quality meets the requirements and the purpose of real-time imaging is achieved.

Frequency diverse array (FDA) radar can form range-angle dependent beampattern, which has good anti-jamming ability. When the direction of the interference fluctuates and the desired signal steering vector mismatches, the traditional null broadening algorithm based on phased array (PA) radar can only widen the null in the angle dimension. A null optimization method with adaptive beamforming for FDA is proposed in this paper. The method is based on a uniform linear array and can form a range-angle two-dimensional adaptive beam. The main lobe of the beam is aimed at the target and the null is aimed at the interference. Then the covariance matrix taper (CMT) algorithm is used to broaden and deepen the null at the position of the interference. Experimental results illuminate the feasibility and effectiveness of the proposed method.

Deception against inverse synthetic aperture radar (ISAR) has been a topic of active research in electronic warfare. However, most of the studies mainly focus on producing one-dimensional deception, which is inadequate for two-dimensional imaging system like ISAR. Thus, in this letter, a joint two-dimensional ISAR deception based on frequency diverse array (FDA) and interrupted sampling is proposed. Compared with conventional phased-array (PA) and single-channel methods, FDA permits more degrees of freedom in producing range deception. Combined with interrupted sampling in the slow time domain, the proposed method is anticipated to produce a group of false targets in both range and cross-range directions. The benefit is easy to control the number and distribution of false targets with high efficiency and less computation burden. Simulation results verify the effectiveness of the proposed method.

In this paper, the sparse stepped frequency synthetic aperture radar (SAR) imaging under basis mismatch is investigated. The traditional CS imaging quality decreases significantly during the target point being not on the grid point. Thus an adaptive basis constructed by the frequency shift within one grid is proposed to reduce the mismatch error and recover the off-grid targets accurately. An efficient algorithm of orthogonal matching pursuit is applied in this paper to solve the sparse regularization problem. Simulation results based on two-dimensional sparse data verify the feasibility of the proposed method.

Since many target features can be acquired via inverse synthetic aperture radar (ISAR), the key of implementing deception jamming on ISAR lies in inducing decoy images imitating the scattering features of real target. In this paper, based on the combination of the frequency diverse array (FDA) and scatter-wave jamming (SWJ), an approach producing multiple two-dimensional decoy images with real target features is presented, the distribution and number of which can be arbitrarily manipulated through designing FDA parameters. Details of the jamming on ISAR is provided along with the simulation results, which illuminates the feasibility and validity of the proposed method.

This paper is devoted to the research of methods and experiments of regularization deconvolution theory on the azimuth super-resolution of forward-looking imaging radar. L1 norm is usually used as a regular term to obtain a stable solution due to its strong resolving power for sparse targets. However, deconvolution is an ill-posed problem, in the process of deconvolution iteration, using the L1 norm as a regular term is sensitive to noise and may causes a large deviation between the solution and the true value due to the influence of noise. This paper proposes the super-resolution imaging method combined truncation singular value decomposition (TSVD) with L1 norm constraint. At lower SNR, this method effectively solves the problem of noise amplification during deconvolution iteration. The effectiveness and advancement of the proposed algorithm are verified by simulation results.

Most of the existing deception jamming methods can only achieve effective jamming on one dimension. Thus, a two-dimensional deception jamming method for SAR imaging based on the frequency diverse array (FDA) and micro-motion modulation is proposed in this paper. The proposed method can produce a number of false targets in both the range and azimuth of SAR image, the location and number of which can be specifically controlled. Based on SAR imaging geometry, principles of the jamming are derived. According to the final image expression, jamming performance with different parameters are demonstrated. Experimental results illuminate the feasibility and effectiveness of the proposed method.

In this paper a new and robust algorithm is proposed to achieve high resolution for inverse synthetic aperture radar (ISAR) imaging in the compressive sensing (CS) framework. Traditional CS based methods have to assume that unknown scatters exactly lie on the pre-divided grids, otherwise their reconstruction performance dropped significantly. So the basis shift algorithm is presented to provide performance improvement of the image reconstruction for off-grid target. The effectiveness and feasibility of the proposed method are investigated by the simulation results.

High speed MIMO radar system, especially for distributed space-borne radar system, brings large Doppler shifts to radar echoes. In order to search for a set of orthogonal waveforms with low Doppler sensitivity in a shared bandwidth, a waveform set design method by using multiple frequency slopes(MFS) is presented. Firstly, we investigate the autocorrelation function (ACF) and cross-correlation function (CCF) for MFS waveforms. It is deduced that the CCF of MFS waveforms changes distinctly with different step of frequency slope. Secondly, we employ ambiguity function to analyze Doppler sensitivity of the proposed waveforms. The analytical expressions between the waveform parameters and the Doppler shift are derived. Finally, the MFS waveforms for distributed space-borne radar system are designed and it is shown from the simulation results that the designed waveforms can meet the requirements of good orthogonality and low Doppler sensitivity simultaneously.