Beampattern Nulls Research Articles

Secure beamforming and power‐efficient artificial‐noise optimization for multibeam directional modulation

AbstractIn this article, an anti‐eavesdropping zero‐forcing plus power‐efficient artificial‐noise optimization method for multibeam directional modulation (DM) synthesis is proposed. It aims to prevent known and unknown eavesdroppers intercepting useful signals as far as possible and achieve a narrower bit error rate (BER) main beamwidth under the premise of limited artificial‐noise (AN) power consumption. Beam pattern nulls are generated in known eavesdroppers directions by utilizing the orthogonality of zero‐forcing beamforming. Low‐sidelobe beamforming is also introduced to DM for the first time to suppress unknown eavesdroppers outside main lobes. The distribution of AN power in all directions is optimized by minimizing the AN transmit power subject to a series of secrecy rate (SR) constraints. Simulation results show that the proposed method outperforms the state‐of‐the‐art DM synthesis methods with regard to power efficiency, SR and BER performance.

Reduced‐dimension STAP using a modified generalised sidelobe canceller for collocated MIMO radars

This study addresses the problem of beam-space post-Doppler reduced-dimension (RD) space-time adaptive processing (STAP) using a modified generalised sidelobe canceller (GSC) in an airborne collocated multiple-input multiple-output (MIMO) radar. Steering vectors corresponding to the nulls of beamforming are used to construct the blocking matrix (BM) of the GSC processor with optimal signal to clutter plus noise ratio. However, it is difficult to determine the beampattern nulls for a collocated MIMO radar which is equivalent to a virtual array with coherent amplitude weights. To build a valid BM of the GSC-based STAP processor, the authors propose a BM modification method based on the modified Gram-Schmidt orthogonalisation algorithm. The authors prove that the modified RD-GSC processor can achieve the performance equal to that of the fully optimal processor conditionally. The authors also show that the proposed method has reduced computational complexity and fast convergence rate. Numerical simulations are presented to demonstrate the effectiveness of the proposed methods.

Grating lobe prediction and deconvolution for synthetic aperture sonar

Synthetic aperture sonar (SAS) arrays are typically undersampled in the sense that the array element spacing is much larger than the acoustic wavelength. Grating lobes are suppressed by making a judicious choice of beampattern nulls for the transmit and receive elements, such as a 3:2 ratio for the length of the transmit and receive elements. However, grating lobe artifacts can appear in SAS imagery when the target strength difference between a highly reflective object and the surrounding seabed exceeds the sidelobe level of the synthetic array. We present a theoretical model of the SAS point scattering function (PSF) that takes into account shaded element beampatterns for a multichannel SAS array. The PSF model is validated using experimental data from AquaPix, a wideband 300 kHz interferometric SAS. In practice, observed SAS images are described by the convolution of the seabed reflectivity with the PSF. Therefore, knowledge of the PSF facilitates the removal of grating lobe artifacts using deconvolution techniques such as the Richardson-Lucy algorithm. Conventional and deconvolved SAS images of a highly reflective target are presented to demonstrate the effectiveness of deconvolution based on the modeled PSF.

Optimum Partitioning of a Phased-MIMO Radar Array Antenna

In a phased-multiple-input-multiple-output radar, the transmit antenna array is divided into multiple subarrays that are allowed to be overlapped. In this letter, a mathematical formula for optimum partitioning scheme is derived to determine the optimum division of an array into subarrays and number of elements in each subarray. The main concept of this new scheme is to place the transmit beam pattern nulls at the diversity beam pattern peak sidelobes and place the diversity beam pattern nulls at the transmit beam pattern peak sidelobes. This is compared to other equal and unequal schemes. It is shown that the main advantage of this optimum partitioning scheme is the improvement of the main-to-sidelobe levels without reduction in beam pattern directivity. Also, signal-to-noise ratio is improved using this optimum partitioning scheme.

Double zero minimum variance distortionless response beamformer

Adaptive beamformers (ABFs) place deep beampattern notches near interferers to suppress the interferers' power in the ABF output. The common sample matrix inversion (SMI) Minimum Variance Distortionless Response (MVDR) ABF computes the beamformer weights by substituting the sample covariance matrix (SCM) for the unknown ensemble covariance matrix in the MVDR expression. Errors in the SCM estimate of interferer direction due to limited sample support or interferer motion degrade the ABFs ability to suppress the interferer. This presentation exploits array polynomial properties to design a robust ABF. The array polynomial for a uniform linear array beamformer is the z-transform of the array weights. The array polynomial zeros on the unit circle correspond to the beampattern nulls. The proposed double zero (DZ) MVDR ABF solves for the MVDR weights using the SCM for a half-aperture subarray, then convolves the half-aperture weights with themselves to obtain the full aperture ABF weights. The resulting array polynomial for the DZ MVDR ABF has second-order zeros, producing broader and deeper notches in the interferer direction. The DZ MVDR ABF outperforms the SMI MVDR and covariance matrix tapered ABFs in simulations with stationary and moving interferers. [Work supported by ONR 321US.]

전기적 빔 조향기반의 기지국 안테나에 관한 연구

Abstract In this paper, we propose an electrically tilting system based on a null-steering in order to solve the problem of the shadowing loss caused by the mechanically tilted antenna system in mobile services. Especially, we improve the downward shadowing loss by eliminating or moving the vertical beampattern nulls between — 30° ～ 0° to be able to tilt the downward beampattern between — 10° ～ 0°. The antenna has 14.5 dBi gain and side lobe level (SLL) is lower than — 18 dB within downward tilting range. The isolation of polarization is greater than 30 dB when running in electric tilt down to — 10°. To verify this paper, we made the base-station antenna for W-CDMA and beam tilting devices, and verified the performances.Key words : Null-Steering, Electrical Tilt, Base Station Antenna, Phased Array, W-CDMA 「이논문은2011년도광운대학교교내학술연구비지원에의해연구되었음.」 광운대학교전파공학과(Department of Wireless Communication Engineering, Kwangwoon University) *서울시립대학교전기전자컴퓨터공학부(Department of Radio Science & Engineering, University of Seoul)․Manuscript received June 5, 2012 ; Revised August 27, 2012 ; Accepted September 5, 2012. (ID No. 20120605-068)․Corresponding Author : Young Seek Chung (e-mail : yschung@kw.ac.kr)

Model-Based Subspace Projection Beamforming for Deep Interference Nulling

This paper considers the problem of adaptive array processing for interference canceling to drive very deep nulls in difficult signal environments. In many practical scenarios, the achievable null depth is limited by covariance matrix estimation error leading to poor identification of the interference subspace. We address the particularly troublesome cases of low interference-to-noise ratio (INR), relatively rapid interference motion, and correlated noise across the receiving array. A polynomial-based model is incorporated in the proposed algorithm to track changes in the array covariance matrix over time, mitigate interference subspace estimation errors, and improve canceler performance. The application of phased array feeds for radio astronomical telescopes is used to illustrate the problem and proposed solution. Here even weak residual interference after cancellation may obscure a signal of interest, so very deep beampattern nulls are required. Performance for conventional subspace projection (SP) is compared with polynomial-augmented SP using simulated and real experimental data, showing null-depth improvement of 6 to 30 dB.

Dominant mode rejection beamformer notch depth: Theory versus experiment

The dominant mode rejection (DMR) adaptive beamformer attenuates loud interferers by directing beampattern nulls toward signals contained in the dominant subspace [Abraham/Owsley, Proc. Oceans, 1990]. The dominant subspace is defined by the eigenvectors associated with the largest eigenvalues of the sample covariance matrix. DMR performance is primarily determined by how closely the eigenvectors of the sample covariance matrix match the true interferer directions. Random matrix theory (RMT) describes how the accuracy of the sample eigenvectors varies with the interferer-to-noise ratio (INR), array size, and the number of snapshots used to estimate the sample covariance. A simplified analytical model based on RMT predicts the mean DMR notch depth as a function of INR, array size, interferer location and the number of snapshots. This talk compares the RMT predictions with experimental results obtained by cancelling array strum in data from a vertical array deployed in the Philippine Sea. The array strum interference predominantly falls within the subspace spanned by the first two eigenvectors of the covariance matrix. Notch depth statistics obtained using a large set of receptions show good agreement between theory and experiment. [Work supported by ONR.]