A Mainlobe Interference Suppression Algorithm Based on Bistatic Airborne Radar Cooperation

In order to solve the problem of mainlobe interference in small hydroacoustic array signal processing, this paper proposes a beamforming method based on the high-resolution direction of arrival (DOA) estimation and interference coherence matrix (ICM) reconstruction. The DOA estimation is first performed using an improved sparse iterative covariance-based (SPICE) method, unaffected by the coherent signal, and it can provide highly accurate DOA estimation for multiple targets. The fitted signal energy distribution obtained from the SPICE is then utilized for the reconstruction of the signal coherence matrix. The reconstructed ICM matrix is used to construct a blocking masking matrix and an eigen-projection matrix to suppress the mainlobe interference signal. Compared with existing methods, the method in this paper possesses better mainlobe interference suppression ability. Within the mainlobe interference interval angle of 3° to 13.5° from the signal of interest (SOI) based on eight-element uniform linear arrays, the method in this paper can enhance the signal-to-interference ratio (SIR) by about 15.59 dB on average compared with the interference-free suppression of conventional beamforming (CBF) and outperforms the other interference suppression methods simultaneously. Simulations and experiments demonstrate the effectiveness of this method in mainlobe interference scenarios.

Here a novel mainlobe interference suppression technique based on eigenprojection algorithm and beam pattern similarity constraints is proposed. This method can effectively suppress the multiple mainlobe interferences and sidelobe interferences. The output of adaptive beamforming is calculated via adaptive weight vector obtained by the convex objective function and processed echo data based on the eigenprojection matrix. The simulations have been presented to evaluate the theoretical analysis.

A mainlobe interference suppression method is proposed based on eigen-projection processing and covariance matrix reconstruction. In the proposed method, the eigen-projection matrix is calculated based on the eigenvector of mainlobe interference to suppress the mainlobe interference in received echo data. The interference covariance matrix is reconstructed after the eigenvalue of mainlobe interference is replaced by the average value of noise eigenvalues to eliminate the effect of mainlobe interference to adaptive weight vector. Finally, the output of adaptive beamforming is calculated by processed echo data and adaptive weight vector obtained based on reconstructed covariance matrix. Simulation results show that the proposed method can suppress the mainlobe interference effectively and achieve excellent performance .

In over-the-horizon radar systems, much interference comes from the mainlobe direction, which reduces the radar performance. In this paper, multiple-input multiple-output radar technologies are introduced to suppress the mainlobe interference in an OTHR system. Based on the transmit beamforming at the receiver, the mainlobe interference can be suppressed completely, and simulation results validate this approach.

Chapter 3 - Theory of monostatic and bistatic radar systems

The article discusses the issues of building bistatic radar systems, which are supposed to be used in the National Guard of Ukraine to perform tasks for the protection of important state facilities. The peculiarities of the construction of this system are associated with the absence of its own transmitter in its composition and the use of the «translucent» location effect. A general configuration of bistatic coherent radar systems is proposed and the main problems of signal processing in such a radar system are considered. The central problem of constructing this bistatic radar system is the effect of an interfering direct signal from a radiation source (usually continuous), penetrating into the receiving path along the side lobes of its antenna. Using analytical expressions, the dependences of the ratio of the power of the useful and penetrating signals for delivery vehicles and intruders on the azimuth of the target relative to the receiver at various fixed ranges are obtained. The analysis of the dependences showed that at ranges to the target less than 5 km, the ratio of the signal capability does not depend on the target azimuth. With an increase in the detection range and an  increase  in the azimuth of the target, the signal power  ratio  tends,  respectively,  to -65 dB for delivery vehicles and -90 dB for intruders. Ways of suppressing the direct signal are considered. To improve the suppression of such a signal, an adaptive compensator as part of the receiver is proposed. It consists of a feedback control system and takes into account the ratio of the useful and penetrating signals, information about their delay and structure. The general structure of a receiver with a compensation system for a penetrating signal and a block diagram of an adaptive compensation device are presented. Direction for further research. Particular attention should be paid to defining the characteristics of the bistatic covert surveillance system in terms of compensating for the influence of the underlying surface and local objects.

Amainlobe interference suppression method is proposed in this paper, which can still work when the signal of interest (SOI) is present in the training data. In this method, the iterative adaptive approach (IAA) is applied to spatial spectrum estimation at first. Then, IAA spatial spectrum is used to reconstruct the interference-plus-noise covariance matrix (INCM). Next, the eigenvector associated with mainlobe interference in INCM is determined and the eigen-projection matrix can be calculated to suppress the mainlobe interference. Meanwhile, the sidelobe-interference-plus-noise covariance matrix (SINCM) can be reconstructed. Finally, the adaptive weight vector is obtained. One main advantage is that the proposed method can deal with coherent mainlobe interference and sidelobe interferences simultaneously. Simulation results demonstrate the effectiveness of the proposed method.

Beamspace MUSIC (multiple signal classification) of forward-backward spatial smoothing are used to estimate the directions of coherent arrivals. Coherence are often encountered in sonar, radar, or mobile communications. Such combination can be degraded when the source signals become coherent or strongly correlated. In this paper, we improve angular resolution of beamspace MUSIC by using the forward-backward averaging of a combined signal eigenvectors. The sample covariance matrix computed from the forward-backward spatial smoothing is exploited for an eigen-decomposition. The decorrelation performance of the proposed method is compared to the several methods based on MUSIC and on beamspace MUSIC, in terms of directions of arrival (DOA) estimations, MSEs versus (1) correlation, (2) noise variance and (3) SNRs, probability of resolution to separate closely spaced DOAs.

Compressive radar imaging has attracted considerable attention because it substantially reduces imaging time through directly compressive sampling. However, a problem that must be addressed for compressive radar imaging systems is the high computational complexity of reconstruction of sparse signals. In this paper, a novel algorithm, called two-dimensional (2D) normalized iterative hard thresholding (NIHT) or 2D-NIHT algorithm, is proposed to directly reconstruct radar images in the matrix domain. The reconstruction performance of 2D-NIHT algorithm was validated by an experiment on recovering a synthetic 2D sparse signal, and the superiority of the 2D-NIHT algorithm to the NIHT algorithm was demonstrated by a comprehensive comparison of its reconstruction performance. Moreover, to be used in compressive radar imaging systems, a 2D sampling model was also proposed to compress the range and azimuth data simultaneously. The practical application of the 2D-NIHT algorithm in radar systems was validated by recovering two radar scenes with noise at different signal-to-noise ratios, and the results showed that the 2D-NIHT algorithm could reconstruct radar scenes with a high probability of exact recovery in the matrix domain. In addition, the reconstruction performance of the 2D-NIHT algorithm was compared with four existing efficient reconstruction algorithms using the two radar scenes, and the results illustrated that, compared to the other algorithms, the 2D-NIHT algorithm could dramatically reduce the computational complexity in signal reconstruction and successfully reconstruct 2D sparse images with a high probability of exact recovery.

In the increasingly complex electromagnetic environment, main lobe jamming significantly degrades the performance of a wideband radar system. To mitigate this issue, this paper developed a wideband main lobe jamming suppression algorithm based on a distributed array radar. Firstly, this algorithm utilizes eigen-projection matrix processing in the main array to cancel out the main lobe jamming for main lobe maintenance, and then suppresses side lobe jamming through null constraint beamforming. Subsequently, the large aperture of the full array is leveraged to form a narrow beam directed toward the main lobe interference. Finally, joint beamforming using the minimum mean square error criterion is employed. In scenarios where both main lobe jamming and side lobe jamming exist, this algorithm can adaptively cancel main lobe wideband jamming, suppress side lobe wideband jamming, and effectively control the significant loss of the desired wideband signals caused by main lobe jamming within a smaller angular range. Simulation results validate the effectiveness of the algorithm.

The feasibility of the estimation of a target’s coordinates solely from the Doppler data measured by forward-scatter radar systems (RSs) is analyzed. It is shown that the coordinates’ ambiguity is inherent in a bistatic RS with one transmitting antenna and one receiving antenna. This ambiguity is eliminated in a system with one transmitting antenna and two receiving antennas located close to each other. Algorithms for determining the target’s coordinates in this system are proposed. The accuracy of estimating the target’s coordinates is evaluated and compared to that obtained with a bistatic RS that measures the Doppler frequency and a signal’s direction of arrival.

Radar networks can provide spatial diversity by observing targets from different perspectives with adequately separated receiving stations. This article proposes a mainlobe interference suppression approach for radar networks based on covariance matrix reconstruction. First, we formulate the mainlobe interference suppression under multiradar configuration as a multichannel signal enhancement problem and perform range and Doppler equalization to improve interferences’ spatial correlation. Then, we estimate the signal and interference covariance matrix from the sampling covariance matrix by solving a robust principal component analysis (RPCA) model. After that, we devise a time-domain-constrained (TDC) linear estimator dependent on the reconstructed covariance matrices to enhance target echo. To remove those duplicate false targets caused by signal enhancement and estimate the state of the physical targets, we establish and solve a generalized multiple measurement vector (GMMV) model based on the fact that targets have unique locations in the state space. Finally, we confirm the effectiveness of the proposed approach with numerical experiments and demonstrate better performance in comparison with the subspace projection method.

Mixed source localization plays an important role in passive radars. Aiming at the problem of low accuracy via phase difference method under a uniform circular array, this paper proposes a matrix differencing method for mixed far-field and near-field source localization. First, a two-dimensional MUltiple Signal Classification (MUSIC) method was utilized to estimate the azimuth and elevation angles of far-field sources. Thereafter, the covariance matrix difference method was exploited to extract the difference matrix of near-field sources. The azimuth and elevation angles of the far-field sources were estimated using the Estimation of Signal Parameters via Rotational Invariance Techniques-like (ESPRIT-like) method. Furthermore, the distance of the near-field sources was obtained by the one-dimensional MUSIC method. Finally, simulations were performed to verify the performance of the proposed algorithm. The proposed algorithm could effectively identify the mixed source when the two-dimensional Direction-Of-Arrival (DOA) of the far-field and near-field sources were the same. Moreover, the proposed algorithm could improve the accuracy of the mixed source parameter estimation. Results show that when the signal-to-noise ratio was set to 20 dB, the 2-D DOA estimation error of the near-field source was approximately 0.01°, and the distance error of the near-field source was approximately 0.1 m.

Calibration considerations and the performance analysis of an L-band airborne clutter measurement system are discussed. The measurement system is designed to collect simultaneous bistatic and monostatic clutter measurements in support of the hybrid bistatic radar (HBR) system. The analysis techniques used to define the experiment geometry and resulting resolution cells, calibration considerations, and the impact on the ability to determine clutter radar cross sections are described. The calibration techniques selected involved the transfer of calibration data from optimal geometries for calibration, to the geometries of interest in this program. >

In this contribution, we investigate on the coherent bistatic scattering generated by a radar system when illuminating a rough surface. Moving from the well-known scattering theory based on the Kirchhoff approximation, we propose an extended formulation of the Fung-Eom model, by introducing a higherorder expansion on the phase term of the impinging spherical wave. We demonstrate and discuss the importance of such correction for the accurate characterization of the coherent scattering generated in bistatic radar system. We give insight, for the first time, on the role played by both the antenna pattern and the wavefront sphericity in bistatic scattering in the whole incidence plane, not limiting the analysis to the backscattering and specular directions. This is particularly important for practical applications, such as the modeling of the scattering generated by sources of opportunity.