Peak Sidelobe Ratio Research Articles

Probability of defect detection in pulse compression favourable thermal excitation schemes for infra‐red non‐destructive testing

InfraRed non-destructive testing and evaluation (IRNDT&E) has emerged as a promising approach for non-destructive testing and evaluation (NDT&E) of various materials because of its inherent merits such as remote, non-invasive, qualitative as well as quantitative inspection capabilities. Among the various IRNDT&E techniques, recently proposed modulated pulse compression favourable thermal wave imaging (PCTWI) techniques, especially frequency modulated thermal wave imaging (FMTWI) and its digitised version digitised FMTWI (DFMTWI) have gained popularity over the conventional sinusoidal modulated [lock-in thermography (LT)] and pulse-based thermographic techniques [pulse thermography (PT) and pulse phase thermography (PPT)] by providing better depth resolution, in less experimentation time, using low peak power excitation heat sources. The present work highlights a comparative study on highly depth resolved continuous depth scanning PCTWI techniques, with single frequency thermal excited LT, on the basis of defect detection probability. The proposed study has been carried out on a glass fibre reinforced polymer test sample with Teflon inserts as defects by considering peak side lobe ratio as a figure of merit. The experimental results clearly show that the probability of detection of defects for DFMTWI is far superior as compared to FMTWI and LT.

An efficient and accurate three-dimensional imaging algorithm for forward-looking linear-array sar with constant acceleration based on FrFT

Linear-array synthetic aperture radar can break through the limitations of traditional SAR on 3-D forward looking imaging, which continues to attract the worldwide attention, especially on 3-D topographic mapping and aircraft blind landing. To overcome the large range migration and strong space-variant characteristic caused by the uniformly accelerated SAR platform, a new 3-D fractional chirp scaling algorithm (FrCSA) for forward looking linear-array SAR with constant acceleration is proposed in this paper. Based on the novel geometry configuration and the equivalent hyperbolic signal model, a chirp scaling operation is employed to compensate the range dependent range cell migration (RCM). Meanwhile, the FrFT tool is introduced to achieve much more accurate focusing. The 3-D imaging results of 3 × 3 × 3 array point scatterers indicate that the proposed method can achieve better focusing capabilities, greater peak side-lobe ratio (PSLR) and integrated side-lobe ratio (ISLR) comparing with the traditional CS algorithm based on FFT.

SVD-Based Ambiguity Function Analysis for Nonlinear Trajectory SAR

A nonlinear trajectory of a radar platform in synthetic aperture radar (SAR) may lead to severe coupling between the range and the azimuth, which may make the ambiguity function (AF) analysis complicated. The numerical algorithm-based AF analysis may be computationally expensive, while the existing analytical algorithm-based AF analysis may cause large errors because it does not consider the coupling between the range and the azimuth. By observing that the singular value decomposition (SVD) is good to deal with the coupling problem, in this article, we propose an effective AF analysis based on SVD. The key idea is to first use a small amount of sampling points for SVD of the coupled term in the AF and then the decoupled vectors are fitted to high-order polynomials for the analytical AF calculation. It converts the double integral into the product of two single integrals in the calculation. From the proposed SVD-based AF analysis, three parameters, namely, 3-dB resolution, peak sidelobe ratio (PSLR), and integrated sidelobe ratio (ISLR), are then effectively computed. The simulated results verify the good performance of the proposed SVD-based AF analysis.

Design and analysis of an 8‐element dipole array for passive coherent location systems

AbstractThis article deals with a design and analysis of an 8‐element dipole array for passive coherent location (PCL) systems. The array is composed of eight identical dipole elements that are arranged at a radius of 0.5λ0 from the center to the elements. To verify the performance for the PCL system, the array is fabricated and measured in an outdoor test site. Array performances such as the antenna gain, peak to side lobe ratio (PSLR), half‐power beam width (HPBW), null width, and null depth are then analyzed. The results demonstrate that the proposed array has beam pattern characteristics suitable for PCL systems.

Implementation of GOA to Non-Uniform PRI of SFPT for improving Resolution in Radar

Pulse compression techniques are mostly used for increasing range resolution in radar systems. Stepped Frequency Pulse Train (SFPT) signal is well suitable in pulse compression techniques. The Pulse Repetition Interval (PRI) of the SFPT is varied to avoid the blind speed and in Counter Measures. Here, evolutionary algorithms are used to optimize non-uniform PRI sequence of SFPT signal for getting better resolution. The PSLR( Peak Sidelobe Ratio) and ISLR (Integrated Sidelobe Ratio) are the performance measures of the signal. The non-uniform PRI sequence is optimized by Differential Evolutionary Algorithm (DE) but it has several drawbacks including unstable convergence in the last period and easy to drop into regional optimum. To overcome this, Grasshopper Optimizer Algorithm (GOA) is used in this paper for increasing the PSLR of Non uniform PRI SFPT signal.

Encoded Hybrid PSK/FSK Waveform for LPI Radar

Since the advantage of pulse compression radar, the pseudo random codes and poly time codes and non linear frequency modulation has been mostly widely used low probability intercept (LPI) radar waveforms. By changing frequencies time to time in frequency modulation known as non-linear frequency modulation (frequency hopping (FH)), peak to side lobe ratio (PSLR) can be achieved to make less severe the covering effect of nearby targets and to improve the useful dynamic range. Adding an appropriate binary encoded ternary phase shift signal (PSK) as form as Binary encoded Hybrid-PSK/FSK (BEH PSK/FSK), the peak side lobe ratios are obtained very low values (e.g., PSLR<-70dB), similar to the antenna side lobes. In advanced microwave power amplifier technology, now a day’s using low peak to average power modules requires them to be amalgamated at the radio frequency (RF) stage in that way to obtain the required emitted radiated power. The deterministic waveforms are represents Noise waveform radar technology is a valid alternative. The pseudo-random waveform-realization of a noise process, the higher its bandwidth-time (or BT) product, the lower the (numerical) peak side lobe ratio. With practical Bandwidth-time values, the achievable peak side lobe using pure random is not sufficient the generated pseudorandom waveforms undergoes optimized genetic algorithm Hamming Scan (HS) to achieve optimized pseudo random (OBC), in order to achieve the desired side lobe level. This manuscript proposes a general analysis of the two modes of radar waveforms, i.e., Ternary and Binary alphabetic waveforms of coincidence detection.

High-Resolution Radar Waveform Design Based on Target Information Maximization

Although the transmit radar waveform design problem for maximizing target information has been studied widely in the past, the resolution requirement is normally ignored in such designs. Using maximizing target information as a criterion, a new radar waveform design method meeting the high-resolution requirement is proposed in this article, which makes no assumptions on the statistical distribution of target scattering. The objective function is proposed by maximizing the Pearson correlation coefficient and the design is then transformed into an optimization problem, which is solved in two steps. First, a closed-form expression for the discretized waveform with constant power constraint is derived in the time domain. Second, based on the bandwidth analysis of the optimal solution, a resolution improvement method considering information distortion is introduced and a suboptimal waveform is proposed while satisfying the constant power and resolution requirements. Finally, performance of the proposed radar waveform in terms of information acquisition, classification, and resolution is analyzed and compared with the classic high-resolution linear frequency modulated waveform (LFMW). Simulation results show that the resolution of the suboptimal waveform is slightly lower than the LFMW, but more desirable in terms of peak sidelobe ratio, information acquisition, and classification.

Application of optimal FrFT order for improving the azimuth resolution of range Doppler imaging algorithm

The traditional range Doppler (RD) imaging algorithm has become the most intuitive and classical method in synthetic aperture radar (SAR) imaging processing because of its easy implementation and high processing efficiency. However, owing to the poor quality of the image produced by RD algorithm, this traditional imaging method is growing increasingly unable to meet practical needs. In an effort to solve the problem of poor azimuth imaging quality, this study proposes a high-resolution RD azimuth imaging algorithm. The expression of the optimal order of the SAR azimuth signals using fractional Fourier transform (FrFT) is derived in detail herein. A theoretical analysis shows that this optimal order is unique and depends on the azimuth imaging parameters. The experimental results based on airborne SAR simulation data and spaceborne SAR measurement data indicate that the azimuth resolution of the proposed algorithm is improved by 31.6 or 46.8% as against that of the traditional RD algorithm, whereas the peak side lobe ratio (PSLR) and integrated side lobe ratio (ISLR) values obtained via the proposed algorithm are approximately equivalent to those obtained via the traditional RD algorithm.

Optimization of Weighting Window Functions for SAR Imaging via QCQP Approach.

Weighting window functions are commonly used in Synthetic Aperture Radar (SAR) imaging to suppress the high Peak SideLobe Ratio (PSLR) at the price of probable Signal-to-Noise Ratio (SNR) loss and mainlobe widening. In this paper, based on the method of designing a mismatched filter, we have proposed a Quadratically Constrained Quadratic Program (QCQP) approach, which is a convex that can be solved efficiently, to optimize the weighting window function with both amplitude and phase, expecting to offer better imaging performance, especially on PSLR, SNR loss, and mainlobe width. According to this approach and its modified form, we are able to design window functions to optimize the PSLR or the SNR loss under different kinds of flexible and practical constraints. Compared to the ordinary real-valued and symmetric window functions, like the Taylor window, the designed window functions are complex-valued and can be asymmetric. By using Synthetic Aperture Radar (SAR) point target imaging simulation, we show that the optimized weighting window function can clearly show the weak target hidden in the sidelobes of the strong target.

Azimuth Resolution Improvement for Squinted Synthetic Aperture Radar Imaging Based on Matched Slope Filter

Improving the resolution of Synthetic Aperture Radar (SAR) is a major issue that has gained significant attention recently, especially in the squint mode where obtaining high resolution is challenging. Generally speaking, the azimuth and range resolutions can be improvement by applying matched filtering for compressing the signal. Signal compression is a major part of the well-known algorithms such as the Range Doppler algorithm (RDA) and the Chirp Scaling Algorithm (CSA) by which high positioning accuracy and high resolution are obtained. The transmitted signal by SAR is most often in the form of linear frequency modulation (LFM). However, the chirp signal is always generated in the SAR azimuth direction at the receiver. The squint of observation angle of the radar makes the chirp signal non-linear and non-stationary. Consequently, this study particularly focuses on the azimuth signal compression and instead of the Matched Filter (MF) based on Fourier Transform (FT), an alternative Matched Filter is used for signal compression on time-frequency domain that is known as Matched on Slope Filter (MSF). The Matched on Slope Filter improves the effectiveness of the compression in both squint and non-squint modes. The simulation results indicate that the proposed method improves the resolution and decreases the Peak to Side Lobe Ratio (PSLR) in the target detection.

Robust Visual Tracking With Occlusion Judgment and Re-Detection

A detection algorithm is often used to remedy tracking failures in a typical single-target visual tracking algorithm. In practice, when a target is occluded for a long time, neither the tracking module nor the detection module can accurately predict the position of the target. To accurately locate the target, we first introduce the l 1 l 2 loss function to reduce the sensitivity of correlation filter-based method to local occlusion. To solve the instability of algorithms based on the single feature in complex scene, we use the histogram of oriented gradient (HOG) features and color names (CN) features to train a filter respectively, and the fusion weights are calculated according to the difference between the response value of each filter and the expected response value. At the same time, we adaptively update the model online by calculating the sensitivity of different filters. We follow the re-detection idea in long-term tracking, the peak to sidelobe ratio (PSR) is used to judge the serious occlusion, and we use support vector machine (SVM) for re-detection after severe occlusion or target out-of-view. In this paper, 34 sets of sequences are selected to evaluate the proposed algorithm. The sufficient experimental results demonstrate that our algorithm has strong anti-occlusion ability and robustness performance. We compare our proposal with several state-of-the-art algorithms under all the sequences of OTB100, and our algorithm yields highly competitive performance for tracking.

On method of composing low frequency signals based on array structures

Generating low-frequency electromagnetic waves based on high-frequency antenna and illuminating targets with multi-band signals can be an effect way that can not only reduce the physical dimension of a low frequency antenna, but also improve the performance of radar detection. Combining the electromagnetic wave doppler effect principle and the array antenna architecture, a method of generating a low-frequency signal around the illuminated target is proposed based on the controlling of array antenna parameters, including array radiation element signal timing, phase and element spacing. The principles of array parameter design are described. Composite signals are simulated respectively under two typical geometric relationships between targets and array antenna, target located along the array direction and in the direction of 45° scanning angle. The peak sidelobe ratio (PSLR) and integral sidelobe ratio (ISLR) are used to evaluate the quality of the composite signals. Aiming at practical applications, the effects of array element spacing error, phase error and target location error on the composite signal are simulated and analyzed. Under the condition of sparse uniform array, the influence of the radiation element spacing on the composite signal is analyzed. The simulation results show that the harmonic components of the composite signal increase with the radiating element spacing error and phase error growing.

An Analysis of Metaheuristic Algorithms Used for the Recovery of a Failed Antenna Element in an Antenna Array

A ground-based synthetic aperture radar system (GB-SAR) comprising of 12 horn antennas in its transmitter section and 12 Vivaldi antennas in its receiver section is used for the monitoring of the Tessina landslide in Italy and the sinking of the Costa Concordia ship in Italy. Alternate 2×6 geometry of 12 coaxial cavity horn antennas have been proven to yield a higher half-power beamwidth and low peak sidelobe ratio resulting in a better quality of the image captured. This 2×6 planar array, when fed with power according to the Dolph Chebyshev weighting polynomial, removes side lobes entirely and results in an increase half-power beamwidth (HPBW) value. A failure of any single element in the 2×6 array could lead to the alteration of the radiation pattern thereby jeopardizing the monitoring activity. This paper explores the usage of metaheuristic algorithms in order to recover the weight of the principal antenna element of the 2×6 coaxial cavity horn antenna array. The algorithms explored are Gradient Descent, Simulated Annealing, Firefly algorithm, Bat algorithm, Flower Pollination algorithm, Cuckoo search algorithm, and Harmony Search algorithm. Among these ones, the Firefly algorithm performs the best in finding the weight of the failed antenna element of the 2×6 planar array.

Performance of Ternary Sequence using Basic Cuckoo Search Algorithm

Matched filtering is broadly used in various radar applications and communication fields whose output indicates some range sidelobes which may mask some stronger targets. This problem can be overcome by using mismatched filter after the matched filter which increases the performance that is in terms of peak sidelobe ratio. The proposed algorithm is suitable to obtain superior performance in range resolution and detection range simultaneously. The characteristics of chaotic codes such as auto-correlation and cross-correlation are same as random codes. So the input is considered as binary and ternary chaotic sequence which is undergone matched filtering process which is then undergo mismatched filter for further reduction in the sidelobe levels. The design of mismatched filter is adapted with cuckoo search algorithm that uses Lévy distribution. It is observed that the performance of the ternary sequence is significantly improved at the output and this method is extended to various length of ternary sequences.

Simulation and Performance Analysis of Chaotic Sequences using Enhanced Cuckoo Search Optimization Method

The mostdesirable property required for pulse compression is that the output should have low peak sidelobes that prevent weaker targets from being masked off in the nearby strong targets. Pulse compression can be obtained with matched filter. Matched filter is an optimal linear filter used in radar signal processing and various communication fields to increase the signal to noise ratio. The output of matched filter consists of unavoidable sidelobes which causes false alarm for multiple target detection in many radar system design.For this purpose, mismatched filter is used after matched filter. Inthis paper a new method of design of mismatched filter is discussed which reduces these sidelobes in the compressed waveform. Here new version of cuckoo search algorithm is used along with differential evolution techniquefor complete design of proposed filter to compare the performance of chaotic sequence. The performance of pulse compression is measured in terms of peak sidelobe ratio. The simulation results showthatdevelopmentin the performance of chaotic sequence is obtained at the output of cascaded filter. And further improved performance is achieved with adaptive filters.

Adaptive model updating for robust object tracking

In this paper, we exploit features extracted from convolutional neural network (CNN) to be better utilized for visual tracking. It is observed that CNN features in higher levels provide semantic information which is robust to appearance variations. Thus we integrate the hierarchical features in different layers of a deep model to correlation filter tracking framework. More specifically, correlation filters are learned on each layer to encode the object appearance. The peak-to-sidelobe ratio (PSR) is employed to measure the differences between image patches. To leverage the robustness of our model, we develop an adaptive model updating scheme to train the correlation filters according to different response maps. Extensive experimental results on three large scale benchmark datasets show that the proposed algorithm performs favorably against state-of-the-art methods.

Passive beamforming in co-prime sensor arrays using NSCB method under original pattern perturbations minimization

The co-prime sensor array (CSA), which is an effective sparse configuration, has the drawback of generating grating lobes in passive beamforming. To mitigate this problem, we propose a novel method based on null synthesis with cancellation beams (NSCBs) under original pattern perturbations minimization. In this paper we regard the grating lobes as interference signals with known directions. Firstly, the angular location of the grating lobes in the CSA subarrays are analytically extracted. Then, using the NSCBs method, the grating lobes of the subarrays nulled by adaptive weighting of the CSA elements. We have also shown that the original pattern perturbations minimization problem in mean square sense reduces to minimizing the perturbation of the array excitation. The proposed method will be formulated as a quadratic optimization problem, which can be efficiently solved using the method of Lagrange multipliers. The analytical and simulated results demonstrate that the power pattern obtained by the proposed method in the CSA, in terms of side lobe levels, peak side lobe ratio and integrated side lobe ratio, is better than the previous methods, so called product and min processors.

Photonic Generation of NLFM Microwave Pulses From DFB-Laser Chirp

This letter reports the photonic generation of apodized-spectrum non-linear frequency-modulated (NLFM) microwave pulses by using an optical self-heterodyne scheme. The distributed feedback (DFB) laser diode was modeled as a linear time-invariant system, relating modulation current inputs with optical frequency outputs through its transfer function, which was determined with a time-resolved spectroscopy technique. The suitable current stimulus on the DFB-laser diode required to generate radio frequency chirped pulses was calculated. Both up- and down-chirp NLFM signals were experimentally generated, covering radar bands ranging from $L$ -band to part of $Ku$ -band. The experimental results agreed well with the analytical calculations. A simulation of the echo detection of a radar system using the experimentally generated NLFM signals showed that the peak-to-sidelobe ratio (PSLR) of the compressed pulses was 10 dB better than that of LFM signals with the same bandwidth.

Robust visual tracking using self-adaptive strategy

Discriminative correlation filter-based algorithms have recently demonstrated prominent advantages in the community of computer visual tracking, due to their ability to convert ridge regression problems in the frequency domain for creating solutions efficiently, which has attracted a great deal of attention and spurred new research. High precision and robustness have always been the goals of visual tracking. However, during the tracking process, target objects often encounter sophisticated scenarios such as fast motion and occlusion. During this period, erroneous tracking information will be generated and delivered to the next frame for updating; the information will seriously deteriorate the overall tracking model. To address the problem mentioned above, in this paper, we propose an accurate model self-adaptive update method based on a discriminative correlation filter framework. The proposed tracking method is achieved by utilizing the peak score of a response map generated by the discriminative correlation filter as a dynamic threshold with comparisons to its PSR (peak side-lobe ratio) scores, and then the comparative results are used as the differentiated condition for updating the translation filter and scale filter model. In addition, multiple hand-crafted features such as HOG (histogram of oriented gradient), CN (color names), and HOI (histogram of local intensities) are fused self-adaptively for comprehensive feature representation, which further improve tracking performance. We evaluate the performance of the proposed tracker on OTB benchmark datasets; the experimental results demonstrate that the proposed tracker performs favorably against most state-of-the-art discriminative correlation filter-based trackers including some methods follow deep learning paradigm, and the effectiveness of updating the model self-adaptive is verified.

Waveform diversity design for an MIMO SAR system based on an OFDM chirp

Multiple-input multiple-output (MIMO) synthetic aperture radar (SAR) waveform diversity design has drawn extensive attention since it has a great potential in remote sensing. Waveform designing becomes one of the most significant tasks in the MIMO SAR system. In this study, a novel scheme has been proposed to generate four waveforms using an orthogonal frequency division multiplexing (OFDM) chirp waveform. The four waveforms have good auto-correlation properties, ambiguity performance, and a good peak sidelobe ratio. This scheme makes full use of the bandwidth. The orthogonal waveform is demodulated by padding zeros and under sampling in the frequency domain. Simulation results are obtained to validate that more orthogonal waveforms can be produced by our proposal scheme with a comparative performance.