Peak Sidelobe Research Articles

MIMO Radar Waveform Design for Simultaneous Space–Time–Doppler Domain Optimization: Framework and Implementation

Waveform design has become an attractive topic in the field of colocated multiple-input multiple-output (MIMO) radar that allows antennas to transmit different waveforms. Waveform properties of MIMO radar in space, time and Doppler domains determine the performances of resource utilization, interference suppression, and moving target detection. Therefore, simultaneous optimization of multi-domain properties through waveform design is significant to improve the performance of MIMO radar. In this paper, a novel MIMO radar waveform design framework that constrains the beampattern while maximizing the similarity between the designed and desired waveforms is proposed for simultaneous space-time-Doppler domain optimization. To solve the resulting multi-constraint non-convex problem, an efficient beampattern control and similarity maximization (BCSM) algorithm is developed and its convergence is demonstrated. Especially, the coupling problem due to the similarity constraint is handled by transforming the number domain and introducing the proximal algorithm. While reducing the target distortion in mainlobe region and interference in sidelobe region, the proposed method can also maximize the similarity of MIMO transmit waveforms. Numerical simulation results, apart from verifying that the proposed method outperforms existing methods in space-time-Doppler domain, also illustrate the robustness of proposed method in terms of mainlobe width and desired peak sidelobe level (PSL).

A Unified Framework of Doppler Resilient Sequences Design for Simultaneous Polarimetric Radars

Simultaneous polarimetric radars can measure the polarization scattering matrix (PSM) of moving targets within one pulse. The key point is the orthogonal waveform design to reduce the interference caused by the simultaneous transmission and reception. Meanwhile, to ensure the measurement accuracy of moving targets, the Doppler tolerance of the transmitted waveforms is also important. In this article, first, a matched filter (MF) at the receiver is considered and a unified framework with a newly proposed objective function to design Doppler resilient sequences under several constraints is described. The proposed objective function contains the widely used peak sidelobe level (PSL) and the integrated sidelobe level (ISL) as special cases. Meanwhile, a series of constraint conditions, including the unimodular constraint, the uncertainty modulus constraint, and the PAR constraint, is considered. Thereafter, a mismatched filter is considered for further improving the correlation properties and a similar framework for designing the optimal receiving filter at the expense of a controllable signal-to-noise ratio (SNR) loss is proposed. Numerical results are presented to verify the performance of the proposed methods. The designed sequence pair is also implemented on a fully polarimetric system to measure the PSM of a canonical target in the anechoic chamber, and the effectiveness of the proposed framework is verified by using the simultaneous polarimetric radar. It is predicted that the framework has the potential to be applied for other multichannel systems.

Low Sidelobe Quasi-Orthogonal NLFM Waveforms With Reciprocating Frequency Modulation

The difficulty in designing quasi-orthogonal radar waveforms is to ensure low levels of autocorrelation sidelobe peak (ASP) and cross-correlation peak (CCP) under a large number of waveforms. This letter proposes a waveform model with reciprocating nonlinear frequency modulation (RNLFM) for the quasi-orthogonal waveform design. The RNLFM waveform both enjoys the low sidelobe characteristics of nonlinear frequency modulation (NLFM) and high degrees of freedom from reciprocating frequency modulation. A greedy optimization framework is presented to decompose the waveform design problem into two optimization problems that minimize ASP and CCP levels, respectively. Simulation results show that the ASP and the CCP levels of the optimized RNLFM waveforms are reduced by 5.5~9.5 dB and 0.2~2.4 dB respectively, compared with other quasi-orthogonal waveforms under the same waveform number.

Autonomous weld seam tracking under strong noise based on feature-supervised tracker-driven generative adversarial network

Strong noise from complex welding condition such as arc light and splashes lead to high tracking error in vision-based seam tracking. To solve this problem, this paper proposes an autonomous seam tracking method based on DCFnet. A feature-supervised tracker-driven generative adversarial network (FT-GAN) is introduced to repair the noise interfered laser stripe images. A feature supervision module and feature selection module are designed in the feature extraction process of the encoder. In addition, the DCF tracking response loss is added to the loss function, guiding the tracking-oriented feature restoration. During tracking process, images are first repaired images by FT-GAN and automatically tracked with DCFnet for laser feature point. In order to promote tracking performance and reduce extract calculation, the model parameter updating and image inpainting frequency is controlled by the response peak side lobe ratio (PSLR). In experiments, the tracking speed reaches up to 15 fps, and the average error is controlled within 0.236 mm. Test results prove that this seam tracking method performs well in accuracy, efficiency and robustness over traditional methods.

Kernelised correlation filters target tracking fused multi‐feature based on the unmanned aerial vehicle platform

As unmanned aerial vehicle (UAV) emerged as a flexible acquisition system that is widely used in military and civilian fields, efficient target tracking algorithm is in urgent need for UAV-based computer vision. Although research studies have been reported on typical interferences in the tracking process such as scale change, occlusion, distortion etc., some issues still exist for the target tracking algorithm based on UAV vision. This study exploited the features hidden in different colour spaces, and proposed a multi-feature multi-filter fusion tracking method that combines the HSV (hue, saturation and value) colour space with the histogram of oriented gradient (HOG) feature. The HSV colour space is proved to be able to discriminate objects under different conditions. The HOG of each HSV channel is utilised to train Kernelised correlation filters (KCF), respectively. The final tracking result is the candidate result with the biggest peak sidelobe ratio (PSR). Computer simulations proved that the fusion strategy proposed in this study can effectively improve the tracking performance of the tracker especially when the image sequences are interfered by deformation, occlusion, low resolution, etc. The performance of the tracker is also tested on UAV.

Efficient synthesis of concentric ring arrays with machine learning approach

In this paper, we propose an efficient synthesis method based on two-stage optimization to synthesize the concentric ring array (CRA) through exploiting the potential benefits of machine learning approach, called K-Nearest Neighbor-Bagging (K-BAG). In the first stage, the training dataset of K-BAG is obtained through an optimization algorithm to train the K-BAG. After that, in the second stage, the randomly selected geometrical parameters of CRA are input to the trained K-BAG, then the structural parameters and correspondingly simulated results are obtained simultaneously in output, which can acquire better solutions compared with that of only considering optimization algorithm. The proposed method improves simulation efficiency and K-BAG robustness while guaranteeing the peak sidelobe level compared with other optimization algorithms of previous researches.

Low Correlation Interference OFDM-NLFM Waveform Design for MIMO Radar Based on Alternating Optimization.

The OFDM chirp signal is suitable for MIMO radar applications due to its large time-bandwidth product, constant time-domain, and almost constant frequency-domain modulus. Particularly, by introducing the time-frequency structure of the non-linear frequency modulation (NLFM) signal into the design of an OFDM chirp waveform, a new OFDM-NLFM waveform with low peak auto-correlation sidelobe ratio (PASR) and peak cross-correlation ratio (PCCR) is obtained. IN-OFDM is the OFDM-NLFM waveform set currently with the lowest PASR and PCCR. Here we construct the optimization model of the OFDM-NLFM waveform set with the objective function being the maximum of the PASR and PCCR. Further, this paper proposes an OFDM-NLFM waveform set design algorithm inspired by alternating optimization. We implement the proposed algorithm by the alternate execution of two sub-algorithms. First, we keep both the sub-chirp sequence code matrix and sub-chirp rate plus and minus (PM) code matrix unchanged and use the particle swarm optimization (PSO) algorithm to obtain the optimal parameters of the NLFM signal’s time-frequency structure (NLFM parameters). Next, we keep current optimal NLFM parameters unchanged, and optimize the sub-chirp sequence code matrix and sub-chirp rate PM code matrix using the block coordinate descent (BCD) algorithm. The above two sub-algorithms are alternately executed until the objective function converges to the optimal solution. The results show that the PASR and PCCR of the obtained OFDM-NLFM waveform set are about 5 dB lower than that of the IN-OFDM.

Design of QAM-OFDM Radar-Communication Integrated Signal Based on Golay Complementary sequences

The integration of radar and communication is conducive to improving the utilization rate of hardware resources and spectrum. To address the issue that the communication information in orthogonal frequency division multiplexing (OFDM) integrated signal for radar and communication affects detection performance, an OFDM integrated signal for radar and communication based on precoding was proposed. The communication information of the integrated signal was pre-coded by using the Gray Complementary Sequences (GCS) with better correlation performance to improve the performance of the ambiguity function of the integrated signal and its detection ability. Simulation results show that GCS have better correlation performance compared to M and Gold sequences, and the OFDM integrated signal pre-coded by GCS has lower Peak Sidelobes Ratio (PSLR) and comparable radar performance to LFM.

High-precision two-dimensional beam steering with a 64-element optical fiber phased array.

Large-scale optical fiber phased arrays (OFPAs) are capable of realizing high-power lasers and high-speed beam steering, which are widely used in long-distance detection and communication. However, dephasing occurring from optical fiber jitter and power amplifier noise can reduce beam quality and steering precision in applications. We demonstrate a two-dimensional 64-element OFPA system that employs a stochastic parallel gradient descent algorithm to synchronize the phases and thus achieve high-quality multi-beam output. Using multi-beam steering, the total scan time for covering a certain field of view can be shorter compared to single-beam steering. Moreover, an avalanche photodiode array is used to enhance the precision of the voltage for beam steering. Experimental results show that the peak sidelobe ratio of the main beam achieves 23.7 dB, and the speed of the beam steering between two discretionary angles is 128 kHz.

Fast and low grating lobe multi-beam steering with a subarray level unequally spaced optical phased array

A grating-lobe-suppressed optical phased array (OPA) based on an unequally spaced technique is proposed to realize multi-beam steering, in which the multi-beam is achieved using the subaperture (SA) technique. The element distribution in SA is optimized by a modified genetic algorithm to minimize peak sidelobe levels (PSLL). The results show that grating lobes can be well suppressed using the proposed technique within the whole scanning range of the beams. The PSLL of the optimized unequally spaced OPA reaches as low as 0.21 in the ± 5 ∘ beam direction, which is much better than the equally spaced OPA. Simultaneously, multi-beam asynchronous scanning can be achieved, which significantly improves the accuracy and flexibility of beam steering control. Besides, the simulations show that the spacing range between adjacent elements and the element number should be appropriately chosen to achieve better sidelobe suppression and a narrow beam width.

Fast Low-Sidelobe Pattern Synthesis for Linear Array Thinning Utilizing a Modified Iterative Chirp-Z Transform Technique

A novel algorithm is presented for the pattern synthesis of thinning uniformly spaced linear arrays generating a lower peak sidelobe level. The novel algorithm is based on a modified iterative Chirp-Z transform (MICZT) technique integrated with an adaptively changing fill factor mechanism. The iterative Fourier transform (IFT) method has to be performed a large number of independent trials to find the optimum turned “ON” element distribution, but often easily gets trapped in local optima. The MICZT technique is proposed to accelerate the synthesis efficiency and facilitate global convergence. In the proposed technique, the ability to approach the global optimal is embodied in two aspects. On the one hand, array thinning is accomplished by setting the possible element state of “ON” and “OFF” according to the adaptively changing fill factor during each iteration cycle. On the other hand, the initial element distribution during each independent trial is almost a full array. So the thinned array distributions obtained after several iterations can still inherit some excellent characteristics of the full array. Several representative examples of linear array thinning are given to demonstrate the superiority, effectiveness and good robustness of the MICZT technique.

Non-contact phase coded excitation of ultrasonic Lamb wave for blind hole inspection

The combination of air-coupled ultrasonic testing (ACUT) and ultrasonic Lamb wave is featured with long-distance propagation and high sensitivity to discontinuities, which is a promising method for rapid and accurate inspection of plate-like materials and lightweighted structures. However, dispersive nature of Lamb wave, signal attenuation plus inevitable noises would lead to low signal-to-noise ratio (SNR). To address this problem, phase coded excitation and pulse compression technique are proposed in this paper to achieve higher SNR by over 10 dB in received signals. 13-bit and 1-carrier-period Barker code is employed as both main lobe peak and Peak Side-lobe Level (PSL) are relatively high. It is demonstrated that A0 mode Lamb wave has good localization ability for defects based on these SNR-enhanced signals. Furthermore, Damage Index (DI) and modified Reconstruction Algorithm for the Probabilistic Inspection of Damage (RAPID) are applied to realize ultrasonic imaging based defect evaluation. Results show that the imaging results agree well with the actual artificial defects in terms of size and shape. Lamb-wave-based air-coupled ultrasonic testing, combined with DI and ultrasonic imaging algorithm, could be a potential way in the NDT of lightweighted structures.

Gradient-based optimization method for interference suppression of linear arrays by the amplitude-only and phase-only control

Abstract This paper presents a gradient-based optimization method for interference suppression of linear arrays by controlling the electrical parameters of each array element, including the amplitude-only and phase-only. Gradient-based optimization algorithm (GOA), as an efficient optimization algorithm, is applied to the optimization problem of the anti-interference arrays that is generally solved by the evolutionary algorithms. The goal of this method is to maximize the main beam gain while minimizing the peak sidelobe level (PSLL) together with the null constraint. To control the nulls precisely and synthesize the radiation pattern accurately, the full-wave method of moments is used to consider the mutual coupling among the array elements rigorously. The searching efficiency is improved greatly because the gradient (sensitivity) information is used in the algorithm for solving the optimization problem. The sensitivities of the design objective and the constraint function with respect to the design variables are analytically derived and the optimization problems are solved by using GOA. The results of the GOA can produce the desired null at the specific positions, minimize the PSLL, and greatly shorten the computation time compared with the often-used non-gradient method such as genetic algorithm and cuckoo search algorithm.

Emerging Swarm Intelligence Algorithms and Their Applications in Antenna Design: The GWO, WOA, and SSA Optimizers

Swarm Intelligence (SI) Algorithms imitate the collective behavior of various swarms or groups in nature. In this work, three representative examples of SI algorithms have been selected and thoroughly described, namely the Grey Wolf Optimizer (GWO), the Whale Optimization Algorithm (WOA), and the Salp Swarm Algorithm (SSA). Firstly, the selected SI algorithms are reviewed in the literature, specifically for optimization problems in antenna design. Secondly, a comparative study is performed against widely known test functions. Thirdly, such SI algorithms are applied to the synthesis of linear antenna arrays for optimizing the peak sidelobe level (pSLL). Numerical tests show that the WOA outperforms the GWO and the SSA algorithms, as well as the well-known Particle Swarm Optimizer (PSO), in terms of average ranking. Finally, the WOA is exploited for solving a more computational complex problem concerned with the synthesis of an dual-band aperture-coupled E-shaped antenna operating in the 5G frequency bands.

Waveform Design for MIMO Radar based on improved genetic algorithm

Multiple-input-multiple-output (MIMO) radar can transmit and receive different waveforms at the same time, and its waveform design has great freedom. Under the constraints of constant modulus, similarity, integrated sidelobe level (ISL) and peak sidelobe level (PSL), It is a complex nonlinear constraint problem to suppress clutter so as to maximize the signal-to-interference-plus-noise ratio (SINR) in the optimal design of matched output waveform. In this paper, an improved genetic algorithm (IGA) with strong global and local searching ability is obtained by using chaotic map discretization to obtain initialized population, simulated annealing selection operator and adaptive crossover and mutation operator. Simulation examples demonstrate that the proposed algorithm has the advantage of lower computational complexity compared with the existing cyclic algorithms (CA) and primal dual type algorithm (PDT) for MIMO radar waveform design. The optimal waveform obtained has better performance.

Performance Analysis of Sparse Array Designed by Improved Density-Tapered Method

The density-tapered method is a method to simulate amplitude weighting of full array by using the density of antenna element. However, the probability of the existence and non-existence of the element is 0 and 1 respectively, which makes the performance of the side lobe level of the pattern worse than that of the amplitude weighting of full array. In this paper, by improving the density-tapered method, gradual and interdependent density-tapered method is proposed to realize the design of sparse linear array, and the simulation experiments are carried out to compare and analyze the performance of peak side lobe level. The experimental results show that the improved density-tapered method can further reduce the side lobe level of the pattern.

Design of Optimized Coded LFM Waveform for Spectrum Shared Radar System.

To meet the increasing demands for remote sensing, a number of radar systems using Linear Frequency Modulation (LFM) waveforms have been deployed, causing the problem of depleting frequency resources. To address this problem, several researchers have proposed the Spectrum Shared Radar System (SSRS) in which multiple radars share the same frequency band to transmit and receive their own signals. To mitigate the interferences caused by the signal transmission by other radars, SSRS employs orthogonal waveforms that inherit the orthogonality of the waveforms from orthogonal codes. However, the inherited orthogonality of the codes is significantly reduced when incorporating LFM waveforms with the codes. To solve this problem, in this paper, we propose a novel but simple scheme for generating a set of optimized coded LFM waveforms via new optimization framework. In the optimization framework, we minimize the weighted sum of autocorrelation sidelobe peaks () and cross-correlation peaks () of the coded LFM waveforms to maximize the orthogonality of the waveforms. Through computer simulations, we show that the waveforms generated by the proposed scheme outperform the waveforms created by previous proposals in terms of and .

Synthesis of a Sparse 2D-Scanning Array using Particle Swarm Optimization for Side-Lobe Reduction

Synthesis of sparse arrays is a promising area of research for a wide range of applications including radar and millimeter-wave wireless communication. The design goal of array thinning problems is to reduce the number of elements of an array without significantly affecting its performance. This work presents a technique for synthesizing a sparse phased-array antenna from a 16×16 uniform rectangular array (URA). The proposed approach reduces the number of elements by 50% without any significant increase in the peak sidelobe level (PSLL) for all possible scan angles in the azimuthal and elevation plans within a finite range of scan angles. The synthesis includes an artificial neural network (ANN) model for estimation of the excitation weights of the URA for a given scan-angle. The weights of the sparse array are computed by the Hadamard product of the weight matrix of the URA with a binary matrix that is obtained using particle swarm optimization (PSO) to minimize the PSLL.

Beampattern Synthesis via First-Order Iterative Convex Approximation

This letter deals with a shaped beampattern synthesis problem through controlling the mainlobe ripple and the output filter energy based on the minimization of the peak sidelobe level in the spatial region of interest. To tackle the challenging optimization problem with nonconvex constraints, a novel first-order iterative convex approximation (FOICA) procedure that handles the nonconvex constraints with their convex upper bound functions resorting to the first-order Taylor expansion is developed. Hence, in each iteration, the original problem is approximated through a convex problem globally solved via a polynomial time method. Additionally, a nonnegative slack variable to ensure a decreasing trend in the objective function during the iteration is introduced. Finally, the numerical simulations are provided to verify that the proposed algorithm outperforms the state-of-the-art algorithms in terms of achieved beampattern performance.

Thinned linear array using joint optimization of IWDO/FFT algorithm

A sparse array synthesis method based on improved wind-driven optimization algorithm (IWDO) and fast Fourier transform (FFT) for the purpose of sidelobe suppression was introduced. First, the uniform linear array was sparse by the FFT algorithm. Then the amplitude excitation weighting of array elements was optimized by IWDO algorithm based on probability factor chaotic map. During the optimization process, the minimum peak sidelobe level was used as the fitness function. By comparing with the simulation results of classic Chebyshev weighting method, the method proposed in this paper has better performance.