Peak Sidelobe Ratio Research Articles

Three-Dimensional Integral Imaging with Enhanced Lateral and Longitudinal Resolutions Using Multiple Pickup Positions

In this paper, we propose an enhancement of three-dimensional (3D) image visualization techniques by using different pickup plane reconstructions. In conventional 3D visualization techniques, synthetic aperture integral imaging (SAII) and volumetric computational reconstruction (VCR) can be utilized. However, due to the lack of image information and shifting pixels, it may be difficult to obtain better lateral and longitudinal resolutions of 3D images. Thus, we propose a new elemental image acquisition and computational reconstruction to improve both the lateral and longitudinal resolutions of 3D objects. To prove the feasibility of our proposed method, we present the performance metrics, such as mean squared error (MSE), peak signal-to-noise ratio (PSNR), structural similarity (SSIM), and peak-to-sidelobe ratio (PSR). Therefore, our method can improve both the lateral and longitudinal resolutions of 3D objects more than the conventional technique.

Peak Side Lobe Reduction analysis of NLFM and Improved NLFM Radar signal

Signal design is an important component for good performance of radar systems. Here, the problem of determining a good radar signal with the objective of minimizing autocorrelation sidelobes is addressed. Linear Frequency Modulated signal (LFM) is frequently used pulse compression waveform. But using LFM makes it necessary to use weighting techniques in order to reduce the side lobes which considerably decrease the SNR. At the radar receiver, the LFM signal results in first side lobe of -13dB corresponding to the main lobe. This may reduce the resultant SNR usually by 1 or 2dB. In this paper, an attempt is done to design a radar signal to attain low autocorrelation Peak Side Lobe Ratio (PSLR) which exhibits high SNR and high range resolution. In order to maintain high SNR and to get suppressed side lobes of the signal, one can use Non-Linear Frequency Modulation (NLFM). A NLFM signal is designed for different time sweeps called as Improved NLFM. In Improved NLFM the total time sweep and bandwidth are divided into Two Stage and Tri-Stage sweeps NLFM. The quality of the overall best radar signal is assessed through the parameter PSLR for different values of BT. From this analysis, it is found that the tri stage NLFM gives the low PSLR up to -17.62dB. Simulation results shows the reduction in the sidelobe level from LFM to NLFM and in Improved two and Tri-Stage NLFM.

Focus Improvement of Spaceborne-Missile Bistatic SAR Data Using the Modified NLCS Algorithm Based on the Method of Series Reversion

The speed and direction of a missile shifts sharply in the dive phase, making the azimuth frequency modulation (FM) rate change with the azimuthal position, leading to azimuth ambiguities and image distortion. To solve this problem, a modified nonlinear chirp scaling (NLCS) algorithm was adopted to compensate for the azimuth FM rate. First, the geometric configuration and echo signal model of the spaceborne missile bistatic synthetic aperture radar (SAR) were built, and then the Doppler frequency correction was performed, and the 2-D spectrum of the signal was derived by the method of series reversion. Next, range migration correction and range compression were finished in the 2-D frequency domain. Following this, a modified NLCS algorithm was proposed to solve the space variance of Doppler phase problem. After compensating for the azimuth FM rate, the azimuth compression focusing was completed and the imaging result was obtained. Finally, by comparing the calculation amount, imaging effect, and performance index with the traditional NLCS algorithm, it can be concluded that the algorithm reduced the calculation amount by 1.0128 × 108 floating point operations per second (FLOPs) compared with the traditional NLCS algorithm, and the azimuth focusing effect of the edge point was greatly improved. Its resolution, peak sidelobe ratio (PSLR), and integrated sidelobe ratio (ISLR) were improved by 0.87 m, 3.32 dB, and 1.79 dB, respectively, which proved the effectiveness and feasibility of this method.

ECO++: Adaptive deep feature fusion target tracking method in complex scene

Efficient Convolution Operator (ECO) algorithms have achieved impressive performances in visual tracking. However, its feature extraction network of ECO is unconducive for capturing the correlation features of occluded and blurred targets between long-range complex scene frames. More so, its fixed weight fusion strategy does not use the complementary properties of deep and shallow features. In this paper, we propose a new target tracking method, namely ECO++, using deep feature adaptive fusion in a complex scene, in the following two aspects: First, we constructed a new temporal convolution mode and used it to replace the underlying convolution layer in Conformer network to obtain an improved Conformer network. Second, we adaptively fuse the deep features, which output through the improved Conformer network, by combining the Peak to Sidelobe Ratio (PSR), frame smoothness scores and adaptive adjustment weight. Extensive experiments on the OTB-2013, OTB-2015, UAV123, and VOT2019 benchmarks demonstrate that the proposed approach outperforms the state-of-the-art algorithms in tracking accuracy and robustness in complex scenes with occluded, blurred, and fast-moving targets.

Integrated Radar and Communications Waveform Design Based on Multi-Symbol OFDM

Integrated radar and communications (IRC) technology has become very important for civil and military applications in recent years, and IRC waveform design is a major challenge for IRC development. In this paper, we focus on the IRC waveform design based on the multi-symbol orthogonal frequency division multiplexing (OFDM) technique. In view of the defects resulting from high peak-to-mean envelope power ratios (PMEPRs) and high range sidelobes in IRC systems, an intelligent and effective IRC waveform design method jointly optimized with the PMEPR and peak-to-sidelobe ratio (PSLR) is proposed. Firstly, a flexible tone reservation (TR)-based IRC waveform structure is applied in both temporal and frequency domains, i.e., multi-symbol OFDM waveform. Secondly, the optimization problem considering PMEPR and PSLR and extending them to the Lp-norm form is reformulated. Then, the conjugate gradient of the objective function is analytically derived and the conjugate gradient algorithm (CGA) is presented to simultaneously improve the PMEPR and PSLR. Finally, the simulation results show that the proposed algorithm can efficiently generate IRC waveforms with an excellent PMEPR, PSLR, radar signal-to-noise ratio (SNR), and bit error rate (BER) performance.

Drone-Based 3D Synthetic Aperture Radar Imaging with Trajectory Optimization.

This paper presents a trajectory determination and optimization method of multirotors equipped with a single-channel radar to obtain 3D Synthetic Aperture Radar imaging. The result is a realistic trajectory that allows to obtain an imaging of the assumed quality in less time than using a multi-pass trajectory. The optimization criteria, in addition to the cross-range resolution, are the Peak Sidelobe Ratio (PSLR), Integrated Sidelobe Ratio (ISLR), and time of flight. The algorithm is based on a realistic motion model of the radar platform. This paper presents all the steps of the algorithm and provides simulation results that show its practical applicability. The advantage of the presented approach over the existing ones is indicated and further research directions are proposed.

Maximum deviation sliding search based stepped frequency synthesis method for marine vibroseis research

In marine exploration, the shorter emitting time can effectively improve the effects and increase the inversion resolution. In order to reduce the time, stepped frequency synthesis is used for the vibrator in this paper. It can regenerate a wide bandwidth reflect the signal to use multiple narrow bandwidth vibroseis. The effect of phase jump between signals on the peak side lobe ratio of the synthesized signal is analyzed. The reasons for the inaccuracy of phase correction in a practical geological environment are investigated. Finally, the Maximum Deviation Sliding Search method is proposed in this paper. This method is validated to accurately correct the phase of signals in complex subsurface environments. In the experiment, the corrected signal improves the peak partials ratio by 42% and 160% compared with the uncorrected signal.

An Intelligent Vision-Based Tracking Method for Underground Human Using Infrared Videos

The underground mine environment is dangerous and harsh, tracking and detecting humans based on computer vision is of great significance for mine safety monitoring, which will also greatly facilitate identification of humans using the symmetrical image features of human organs. However, existing methods have difficulty solving the problems of accurate identification of humans and background, unstable human appearance characteristics, and humans occluded or lost. For these reasons, an improved aberrance repressed correlation filter (IARCF) tracker for human tracking in underground mines based on infrared videos is proposed. Firstly, the preprocess operations of edge sharpening, contrast adjustment, and denoising are used to enhance the image features of original videos. Secondly, the response map characteristics of peak shape and peak to side lobe ratio (PSLR) are analyzed to identify abnormal human locations in each frame, and the method of calculating the image similarity by generating virtual tracking boxes is used to accurately relocate the human. Finally, using the value of PSLR and the highest peak point of the response map, the appearance model is adaptively updated to further improve the robustness of the tracker. Experimental results show that the average precision and success rate of the IARCF tracker in the five underground scenarios reach 0.8985 and 0.7183, respectively, and the improvement of human tracking in difficult scenes is excellent. The IARCF tracker can effectively track underground human targets, especially occluded humans in complex scenes.

Ensemble Learning-Based Multi-Cues Fusion Object Tracking in Complex Surveillance Environment.

The vast majority of currently available kernelized correlation filter (KCF)-based trackers simply make use of a single object feature to define the object of interest. It is impossible to avoid tracking instability while working with a wide variety of complex videos. In this piece of research, an ensemble learning-based multi-cues fusion object tracking method is offered as a potential solution to the issue at hand. Using ensemble learning to train multiple kernelized correlation filters with different features in order to obtain the optimal tracking parameters is the primary concept behind the improved KCF-based tracking algorithm. After that, the peak side lobe ratio and the response consistency of two adjacent frames are used to obtain the fusion weight. In addition, an adaptive weighted fusion technique is applied in order to combine the response findings in order to finish the location estimation; finally, the tracking confidence is applied in order to update the tracking model in order to prevent model deterioration. In order to increase the adaptability of the revised algorithm to size-change, a Bayesian estimate model based on scale pyramid has been presented. This model is able to determine the optimal scale of the object, which is the goal of this endeavor. The tracking results of a number of different benchmark movies demonstrate that the algorithm that we have suggested is able to effectively eliminate the effects of interference elements, and that its overall performance is superior to that of the comparison algorithms.

Enhancement of three-dimensional image visualization under photon-starved conditions.

In this paper, we propose enhancement of three-dimensional (3D) image visualization under photon-starved conditions using preprocessing such as contrast-limited adaptive histogram equalization (CLAHE) and histogram matching. In conventional imaging techniques, photon-counting integral imaging can be utilized for 3D visualization. However, due to a lack of photons, it is challenging to enhance the visual quality of 3D images under severely photon-starved conditions. To improve the visual quality and accuracy of 3D images under these conditions, in this paper, we apply CLAHE and histogram matching to a scene before photon-counting integral imaging is used. To prove the feasibility of our proposed method, we implement the optical experiment and show the performance metric such as peak sidelobe ratio.

Golay Coding Φ-OTDR With Distributed Frequency-Drift Compensation

The performance of optical-pulse-coding (OPC) phase-sensitive optical time-domain reflectometry ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\boldsymbol {\Phi }$ </tex-math></inline-formula> -OTDR) has been improved significantly in recent years. However, laser frequency drift is still a crucial issue, as it reduces the peak to side-lobe ratio (PSR) in Golay coding <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\boldsymbol {\Phi }$ </tex-math></inline-formula> -OTDR. In this paper, a novel and simple distributed frequency-drift compensation method is proposed. As the phase accumulations of the reference fiber and the sensing fiber are consistent through theoretical analysis and experimental verification, the frequency drift can be compensated by injecting the modulated Golay coding pulses into two fibers at the same time, and subtracting the phase drift of the sensing fiber and the reference fiber. In order to verify the distributed compensation effect, a two-point perturbation measurement experiment is carried out in 9.7 km sensing range. As a result, the far-end signal-to-noise ratio (SNR) is enhanced and the demodulation perturbation SNRs are increased by 2.8 dB and 18.9 dB separately compared with the case without frequency drift compensation. Furthermore, this scheme can also be used in other complex coding systems, providing more possibilities for system designs.

Spaceborne SAR image formation enhancement using MOCO techniques

Synthetic aperture radar (SAR) is considered a prevailing tool for remote sensing. It benefits working with high efficiency in all weather and all-day circumstances, making SAR is very confident compared to other types of remote sensing. The SAR platform moves with constant velocity and height, with a linear path for ideal situations. However, this assumption is not realized in satellite movement, which is an elliptical orbiting that worsens the quality of the focused image. This paper introduces a methodology of motion compensation for motion errors due to satellite elliptical orbiting and perturbations in an orbital path. It represents two major contributions applied on a low earth orbit (LEO) spaceborne SAR. First, motion errors analysis in the range and azimuth directions. Second, an algorithm for motion error compensation (MOCO) combined with a chirp scaling algorithm (CSA) is performed. Moreover, a validation for the formulated algorithm is executed using sentinel-1 level-0 real raw data input, and the result is compared with the sentinel-1 level-1 single look complex (SLC) SAR image. The validation is performed using two different metrics. First, image quality measurement by sharpness, contrast, and entropy. Second, measuring the peak-sidelobe-ratio (PSLR), impulse-response-width (IRW), and integrated-sidelobe-ratio (ISLR) for five high power reflecting points in the scene area.

Fourier Transform of SAR Data Cube and 3-D Range Migration Algorithm

To develop a 3-D imaging synthetic aperture radar(SAR) algorithm, a theoretical expression for a Fourier transform of data cube is required. In this article, we introduce a function representing the Fourier transform of 3-D SAR data cube. The function is derived using the method of stationary phase and similar to the one used for 2-D data matrix. For verification and evaluation, a 3-D range migration algorithm using this function for bulk compression is examined. The simulation results based on the parameters of an experimental terahertz indoor SAR testbed show that the algorithm can well focus the 3-D image and, hence, verify the derived function. The image quality assessments such as spatial resolutions and peak sidelobe ratio are used to further evaluate the function and the algorithm. The measured results are compared with the ones provided by a backprojection algorithm.

Frequency‐domain multireceiver synthetic aperture sonar imagery with Chebyshev polynomials

Based on Chebyshev polynomials, the two-way slant range is first approximated by the fourth-order polynomial approximation. With the series reversion method, the point target reference spectrum (PTRS) which is further used for the development of imaging algorithm in this letter is obtained. The presented method processes the echoed signal corresponding to each transmitter/receiver pair. And then a high-resolution synthetic aperture sonar (SAS) image is obtained by coherently superposing all coarse-resolution images. Comparing the peak sidelobe ratio (PSLR) and integration sidelobe ratio (ISLR), the performance of the presented method is superior to that of the traditional method. Simulations are further validated by the presented method.

Cooperative Automotive Radars with Multi-Aperture Multiplexing MIMO Sparse Array Design

In this paper, a multi-aperture multiplexing multiple-input multiple-output (MAM-MIMO) sparse array is presented for cooperative automotive radars (CARs). The proposed sparse array composed of multiple subarrays can simultaneously cover a wide field-of-view (FOV) and achieve the required azimuth resolution at different ranges. To validate this idea, an optimization model for the MAM-MIMO sparse array is derived based on the example of CARs. This optimization model has been found by combining the peak-to-sidelobe ratio (PSLR) at all beams pointing within the constraints of different detection ranges. In addition, a hierarchical genetic algorithm based on the multi-objective decomposition method has been developed to obtain the optimized sparse array. The proposed method has been evaluated through both simulations and experiments. It is demonstrated that the optimized MAM-MIMO sparse array can effectively suppress sidelobes of its subarrays, yet with reasonably high azimuth resolutions and large FOVs.

Waveform Design for LFM-MPSK-Based Integrated Radar and Communication Toward IoT Applications

The sharing waveform-based integrated radar and communication (IRC) has great potential to apply in Internet-of-Things (IoT) devices due to its equipment miniaturizing and high efficiency of spectrum and energy, etc. However, the sharing waveform scheme demands a tradeoff between radar and communication performances. In this article, we focus on the design of multiple phase-shift keying (MPSK)-based linear frequency modulation (LFM) sharing waveform by exploring the tradeoff among energy leakage, peak-to-side lobe ratio (PSLR), and symbol rate. First, we derive the energy leakage and PSLR with respect to the symbol rate. Next, a novel LFM-MPSK waveform design is carried out by formulating a communication frame-based optimization, where the symbol rate is maximized with the constraints of the energy leakage and PSLR. Then, a branch-and-reduce algorithm is proposed to solve the optimization. Compared with the conventional one, the proposed LFM-MPSK waveform has a higher symbol rate with the same energy leakage and PSLR. Besides, the proposed waveform design alleviates the difficulty of the tradeoff among the energy leakage, PSLR, and symbol rate due to more Pareto solutions. Finally, all the analytical results are validated by simulations.

Coordination of Complementary Sets for Low Doppler-Induced Sidelobes

Golay complementary waveforms are, by definition, able to generate narrow pulses with low sidelobes via coherent signal processing. However, while an ideal impulse can be obtained for target returns at zero-Doppler, significant sidelobes are observed at nonzero Doppler shifts. In this paper, a Generalized Binominal Design (GBD) procedure is proposed for the waveforms consisting of complementary sets in an attempt to reduce the Doppler-induced sidelobes. Our theoretical analysis as well as simulation results show that the proposed approach performs as good as existing Binominal Design method used for sidelobe suppression with Golay complementary waveforms and can also achieve around 28% enhancement on the Doppler resolution, with an acceptable loss in peak to peak-sidelobe ratio (PPSR).

Photonic Millimeter-Wave Joint Radar Communication System Using Spectrum-Spreading Phase-Coding

A novel millimeter-Wave (mm-Wave) joint radar and communication (JRC) system based on photonic spectrum-spreading phase-coding is proposed. The key to the proposed system is the convergence of photonic microwave phase-coding and spectrum-spreading multiplexing techniques. Phase-coding enables the generation of wideband mm-Wave JRC signal, leading to both high range resolution (&#x003C; 3.5 cm) for radar detection and high capacity (&#x003E;1 Gb/s) for wireless communication. The spectrum-spreading multiplexing orthogonalizes the radar signal and communication data, highly reducing mutual interferences. In addition, the spectrum-spreading multiplexing is able to improve both peak sidelobe ratio (PSR) for radar and anti-jamming/anti-noise performance for communication. In the proof-of-concept experiments, a JRC phase-coding signal at 35 GHz is generated. For a 5-Gb/s coding rate, the signal-to-noise ratio (SNR) margin is improved by around 13.8 dB for wireless communication below the pre-forward error correction (FEC) limit, while the PSR reaches &#x007E;12 dB for radar. Moreover, the impact of spreading gain on the communication capacity has been discussed, revealing that an optimized spreading gain should be set to balance the radar and communication performances.

Photonic generation of frequency-tunable biphase and quadriphase coded pulse signals without background interference enabled by vector modulation and balanced detection.

An approach to generating frequency-tunable biphase and quadriphase coded pulse signals without background interference based on a polarization division multiplexing dual-parallel Mach-Zehnder modulator (PDM-DPMZM) is presented and demonstrated. Two ternary baseband code sequences are separately encoded into a pair of orthogonal optical carriers by exploiting a polyphase encoder on the basis of the principle of vector modulation, which in turn can be mapped to the phase shifts of the generated phase coded waveforms after the balanced detection. The frequency tunability can also be achieved by controlling the bias voltage of the associated modulator, so that the carrier frequency can be tuned to either fundamental or doubled frequency. Additionally, by designing different phase codes, the generated pulse signals can be conveniently switched between the quadriphase and biphase coding waveforms. The major advantage of the proposed approach is that four phase shifts can be obtained by simply adjusting the polarity of the ternary code sequences, overcoming the power-dependent limitation of the previous work. A proof-of-principle experiment is conducted to assess the feasibility of the proposed approach built on the Barker code and Frank code phase coded pulse signals generation. Experimental results show the phase coded pulse signals at 12 and 24 GHz carrier frequency are well behaved in terms of peak-to-sidelobe ratio (PSR), range-Doppler coupling and Doppler tolerance.

A Modified PGA for Spaceborne SAR Scintillation Compensation Based on the Weighted Maximum Likelihood Estimator and Data Division

The P-band spaceborne synthetic aperture radar (SAR) is significantly affected by ionospheric scintillation. Although the traditional phase gradient autofocus (PGA) can estimate and compensate the scintillation phase of the single polarization SAR data, the quality of the refocused image will degrade at the scene edge. In this paper, a modified PGA based on the weighted maximum likelihood (WML) estimator and data division is proposed for full-scene image refocusing. First, a data division strategy for scintillation corrupted image is introduced, which is based on the prior scintillation information including its power spectral density (PSD) and autocorrelation function (ACF). Then, some pre-processing steps including data selection, circular shifting and windowing are performed for suppressing the noise and clutter. Finally, the scintillation phase is estimated by the WML estimator with fewer iterations, and after the scintillation phase of all data blocks are obtained, the distorted full-scene image is refocused. Using the generated wide-band ionospheric scintillation model (WBMOD) phase screen, numerical simulations based on point targets and scenes derived from real spaceborne SAR data are carried out. The evaluation results about resolution, peak side-lobe ratio (PSLR), integral side-lobe ratio (ISLR), correlation coefficient and image entropy demonstrate the effectiveness of the proposed algorithm.