Peak Sidelobe Ratio Research Articles

Enhanced range-doppler algorithm for SAR image formation

A Synthetic Aperture Radar (SAR) system is a powerful source of information due to its capability to operate day and night and in all weather conditions. It is essential for military and civilian purposes. Pulse-focusing is employed by the SAR system for achieving both long-range detection and fine-range resolution. The Range-Doppler Algorithm (RDA) is the most popular pulse-focusing technique for creating images from coherent SAR data. Pulse compression techniques for SAR signal processing targets seek to improve map resolution, lower peak power, and increase the Signal-to-Noise Ratio (SNR) of the detected object. This paper demonstrates an enhanced RDA algorithm that uses a modified pulse compression technique based on mismatched filter optimization where Quadratic Constrained Quadratic Program (QCQP) is used. The performance evaluation of the proposed method is performed using visual assessment and the standard image quality metrics peak-side-lobe-ratio (PSLR), impulse-response-width (IRW), and integrated-side-lobe-ratio (ISLR). Simulated and real SAR raw data are used for performance evaluation. The experimental results demonstrate the proposed method’s robustness, efficiency, and reliability in providing a higher-quality SAR image than the traditional RDA algorithm.

Inner-Frame Time Division Multiplexing Waveform Design of Integrated Sensing and Communication in 5G NR System.

The design of an integrated sensing and communication (ISAC) waveform compatible with the 5G new radio (NR) system is crucial in enabling ISAC by utilizing the hardware of existing base stations (BSs). In this paper, we design an inner-frame time division multiplexed sensing waveform in the frame structure of 5G NR to achieve ISAC. The designed waveform is computed by the simulated annealing algorithm on an optimization cost function of a constrained combination of the peak-to-sidelobe ratio (PSLR) and the integrated sidelobe ratio (ISLR) of the velocity ambiguity function. Specifically, the constraints are the 5G communication protocol and 5G NR frame structure. In addition, we conducted corresponding signal detection and estimation methods to illustrate the performance of the sensing waveform. Both theoretical analysis and simulation experiments show that the designed waveform can effectively achieve target detection and parameter estimation under low sensing cost conditions.

Proposed SAR range focusing algorithm based on simulation analysis and SDR implementation

Synthetic aperture radar (SAR) imaging systems use pulse focusing techniques for achieving fine range resolution and large range detection. Stretch processing and correlation pulse focusing techniques are the most popular algorithms used in the radar signal processing stage. The architecture of the stretch processing technique makes it commonly used in frequency modulated continuous wave (FMCW) radar systems due to its simple architecture, low sampling rate, and inexpensive hardware. This paper discusses how the stretch range focusing approach can be used instead of the matched filter technique in the processing stage of the SAR Range-Doppler algorithm (RDA) to generate images of finer resolution and higher quality. In addition, validating the proposed algorithm and evaluating its performance according to some evaluation indices such as peak sidelobe ratio (PSLR), integrated sidelobe ratio (ISLR), and the impulse response width (IRW). Also, this paper presents a comprehensive analysis and hardware implementation of the two SAR algorithms, based on software-defined radio (SDR) architecture where it is characterized by less complexity, low cost, and high flexibility due to the usage of both software data processing and software waveform generation. Two Universal Software Radio Peripheral (USRP-2932) and NI-LabVIEW® software development environment are the platforms used for the hardware validation process. The transmitted waveform is a linear frequency modulated (LFM) signal generated by the first USRP (transmitter) which will hit a target located at a certain distance. The second USRP is used as a receiver for target’s echo processing and detection. This processing stage contains two architectures, which are the matched filter pulse compression architecture and the stretch range focusing approach. Finally, the validation process of the hardware results is performed based on the pre-mentioned evaluation indices.

Three-Dimensional Image Transmission of Integral Imaging through Wireless MIMO Channel.

For the reconstruction of high-resolution 3D digital content in integral imaging, an efficient wireless 3D image transmission system is required to convey a large number of elemental images without a communication bottleneck. To support a high transmission rate, we herein propose a novel wireless three-dimensional (3D) image transmission and reception strategy based on the multiple-input multiple-output (MIMO) technique. By exploiting the spatial multiplexing capability, multiple elemental images are transmitted simultaneously through the wireless MIMO channel, and recovered with a linear receiver such as matched filter, zero forcing, or minimum mean squared error combiners. Using the recovered elemental images, a 3D image can be reconstructed using volumetric computational reconstruction (VCR) with non-uniform shifting pixels. Although the received elemental images are corrupted by the wireless channel and inter-stream interference, the averaging effect of the VCR can improve the visual quality of the reconstructed 3D images. The numerical results validate that the proposed system can achieve excellent 3D reconstruction performance in terms of the visual quality and peak sidelobe ratio though a large number of elemental images are transmitted simultaneously over the wireless MIMO channel.

A sea clutter suppression algorithm for over-the-horizon radar based on dictionary learning and subspace estimation

Detecting a ship target by over-the-horizon radar (OTHR) is seriously affected by sea clutter. This paper proposes a clutter suppression algorithm based on dictionary learning and subspace estimation (DLSE). First, the K-singular value decomposition (K-SVD) is used for dictionary learning and sparse representation of the sea clutter. Then, the orthogonal matching pursuit (OMP) is used to reconstruct the sea clutter component to suppress the outliers. Finally, the clutter covariance matrix is calculated using the reconstructed clutter spectrum, and the clutter subspace of the covariance matrix is estimated to achieve clutter suppression. In this paper, the K-SVD is improved to preserve the phase information of the complex signal. The sea clutter spectrum, after sparse representation and reconstruction, is not impacted by outliers in neighboring cells. Therefore, the clutter covariance matrix has a better estimate accuracy than existing subspace decomposition algorithm. The adaptive parameter estimate method also enhances the adaptability of the DLSE. The experimental results of real data demonstrate that the DLSE is as sophisticated as existing subspace decomposition algorithms while having a higher output signal-to-clutter-plus-noise ratio (SCNR) and peak-to-side lobe ratio (PSLR), improving about 2-5 dB. Results of outlier suppression attest to the robustness of the DLSE. Under various coherent integration times (CIT) and frequencies, the DLSE has the best clutter suppression performance among the comparison algorithms.

Semi-Coprime Array with Staggered Beam-Steering of Sub-Arrays

A split-aperture array (SAA) is an array of sensors or antenna elements in which the array is split into two or more sub-arrays (SAs). Recently proposed SAAs, namely coprime and semi-coprime arrays, offer to attain a small half-power beamwidth (HPBW) with a small number of elements, compared to most conventional unified-aperture arrays, at the cost of reduced peak-to-side-lobe ratio (PSLR). To reduce HPBW and increase PSLR, non-uniform inter-element spacing and excitation amplitudes have proven helpful. However, all the existing arrays and beam-formers suffer increased HPBW, degraded PSLR or both when the main beam is steered away from the broadside. In this paper, we propose staggered beam-steering of SAs, a novel technique for decreasing HPBW. In this technique, we steer the main beams of the SAs of a semi-coprime array to angles slightly different from the desired steering angle. In conjunction with staggered beam-steering of SAs, we have utilized Chebyshev weights to suppress the side lobes. The results show that the beam-widening effect of Chebyshev weights can be mitigated considerably by staggered beam-steering of the SAs. Ultimately, the unified beam-pattern of the whole array offers HPBW and PSLR better than the existing SAAs, uniform and non-uniform linear arrays, especially when the desired steering angle is away from the broadside direction.

Real-time and robust visual tracking with scene-perceptual memory

Unmanned aerial vehicle (UAV) based aerial visual tracking is one of the research hotspots in computer vision. However, the mainstream trackers for UAV still have two shortcomings: (1) the accuracy of correlation filter tracker is greatly improved with more complex model, it impedes accuracy-speed trade-off. (2) object occlusion and camera motion in the aerial tracking scene also seriously restrict the application of aerial tracking. To address these problems, and inspired by AutoTrack tracker, we propose an aerial correlation filtering tracker based on scene-perceptual memory, Fast-AutoTrack. Firstly, to perceive and judge tracking anomalies, such as object occlusion and camera motion, inspired by the peak sidelobe ratio and AutoTrack, a confidence score is designed by perceiving and remembering the changing trend of the confidence and the local historical confidence. Secondly, after tracking anomaly occurring, several search regions are predicted based on the local object motion trend and the Spatio-temporal context information for object re-detection. Finally, to accelerate the model updating, the perceptual hashing algorithm (PHA) is used to obtain the similarity of the search regions between two adjacent frames. On typical aerial tracking datasets UAVDT, UAV123@10fps, and DTB70, Fast-AutoTrack run 71.4% faster than AutoTrack with almost equal accuracy and show favorable accuracy-speed trade-off.

Target parameter estimation for OTFS radar using sparse signal processing

In this paper, we consider a monostatic radar receiver for a joint communication and radar (JCR) system that transmits orthogonal time frequency space (OTFS) frames for target detection and parameter estimation. The circular prolate pulse shape (CPPS) is employed over the OTFS signal as it has lower out-of-band (OoB) power radiation in comparison with the rectangular pulse shaped (RPS) OTFS. The PAPR of CPPS OTFS signal shows lowest value for larger frame duration and hence the signal can be considered to be a good candidate for JCR system. In the Delay-Doppler (DD) domain, the radar channel is sparse and therefore, we model the target detection problem as a sparse recovery problem to generate target profiles with higher peak-to-sidelobe ratio (PSLR). The target detection is carried out in the DD domain, the time–frequency (TF) domain, and in the time domain (TD). Sparse signal recovery algorithms like the orthogonal matching pursuit (OMP) algorithm, the subspace pursuit (SP) algorithm, and the sparse Bayesian learning (SBL) based algorithm are used in target parameter estimation. The performance of these algorithms are compared in terms of their computational complexity, the root mean squared error (RMSE) in the estimates of range and velocity and PSLR value in the target profiles. Simulation results validate that the proposed CPPS OTFS based radar system could detect the targets accurately in all the three domains and produce target profiles with almost zero side lobes.

A sequential constraint relaxation framework to design phase-coded sequences for radar systems

In this paper, the design of phase-coded sequences with good aperiodic autocorrelation properties including peak sidelobe level and integrated sidelobe level for radar systems is considered. The problem is formulated as a rank-one constraint optimization at the design stage. To tackle the resulting non-convex and generally NP-hard optimization problem, an iterative algorithm is developed based on the sequential rank-one constraint relaxation framework, which guarantees a local optimal rank-one solution. The proposed method requires solving a convex problem in each iteration. The procedure can be initialized by dropping the rank-one constraint or using a good sequence in terms of autocorrelation properties. Simulation results show that using the proposed method for finding phase-coded sequences leads to better peak sidelobe ratio and integrated sidelobe ratio for polyphase and binary phase codes compared to previous works in the literature.

Three-Dimensional Digital Zooming of Integral Imaging under Photon-Starved Conditions.

In this paper, we propose new three-dimensional (3D) visualization of objects at long distance under photon-starved conditions. In conventional three-dimensional image visualization techniques, the visual quality of three-dimensional images may be degraded because object images at long distances may have low resolution. Thus, in our proposed method, we utilize digital zooming, which can crop and interpolate the region of interest from the image to improve the visual quality of three-dimensional images at long distances. Under photon-starved conditions, three-dimensional images at long distances may not be visualized due to the lack of the number of photons. Photon counting integral imaging can be used to solve this problem, but objects at long distance may still have a small number of photons. In our method, a three-dimensional image can be reconstructed, since photon counting integral imaging with digital zooming is used. In addition, to estimate a more accurate three-dimensional image at long distance under photon-starved conditions, in this paper, multiple observation photon counting integral imaging (i.e., N observation photon counting integral imaging) is used. To show the feasibility of our proposed method, we implement the optical experiments and calculate performance metrics, such as peak sidelobe ratio. Therefore, our method can improve the visualization of three-dimensional objects at long distances under photon-starved conditions.

Lensless Three-Dimensional Imaging under Photon-Starved Conditions.

In this paper, we propose a lensless three-dimensional (3D) imaging under photon-starved conditions using diffraction grating and computational photon counting method. In conventional 3D imaging with and without the lens, 3D visualization of objects under photon-starved conditions may be difficult due to lack of photons. To solve this problem, our proposed method uses diffraction grating imaging as lensless 3D imaging and computational photon counting method for 3D visualization of objects under these conditions. In addition, to improve the visual quality of 3D images under severely photon-starved conditions, in this paper, multiple observation photon counting method with advanced statistical estimation such as Bayesian estimation is proposed. Multiple observation photon counting method can estimate the more accurate 3D images by remedying the random errors of photon occurrence because it can increase the samples of photons. To prove the ability of our proposed method, we implement the optical experiments and calculate the peak sidelobe ratio as the performance metric.

Performance investigation of an ambiguity function-shaped waveform (AFSW) using a photonics-based radar system.

In this work, we investigate the performance of an ambiguity function-shaped waveform (AFSW) using a millimeter-wave photonics-based radar system at 100 GHz. An AFSW is a radar waveform whose ambiguity function can be shaped to increase the peak-to-sidelobe ratio (PSR) for better detectability of targets in a desired range/velocity region. To the best of the authors' knowledge, this paper is the first in the literature that investigates the performance of such a waveform in a photonics-based radar system. We experimentally compare the AFSW performance to the conventional frequency-modulated continuous wave (FMCW). The experimental results show the ability of the AFSW to achieve a PSR of 38.35 dB compared to the PSR of 14.5 dB obtained using the conventional FMCW. Moreover, we investigate the effects of some optical system impairments on the AFSW, such as: (i) optical modulator nonlinearity, (ii) optical modulator bias drift, and (iii) sampling offset error between the transmitter and receiver.

An adaptive spatiotemporal correlation filtering visual tracking method.

Discriminative correlation filter (DCF) tracking algorithms are commonly used for visual tracking. However, we observed that different spatio-temporal targets exhibit varied visual appearances, and most DCF-based trackers neglect to exploit this spatio-temporal information during the tracking process. To address the above-mentioned issues, we propose a three-way adaptive spatio-temporal correlation filtering tracker, named ASCF, that makes fuller use of the spatio-temporal information during tracking. To be specific, we extract rich local and global visual features based on the Conformer network, establish three correlation filters at different spatio-temporal locations during the tracking process, and the three correlation filters independently track the target. Then, to adaptively select the correlation filter to achieve target tracking, we employ the average peak-to-correlation energy (APCE) and the peak-to-sidelobe ratio (PSR) to measure the reliability of the tracking results. In addition, we propose an adaptive model update strategy that adjusts the update frequency of the three correlation filters in different ways to avoid model drift due to the introduction of similar objects or background noise. Extensive experimental results on five benchmarks demonstrate that our algorithm achieves excellent performance compared to state-of-the-art trackers.

Constrained radar waveform optimization for a cooperative radar-communication system

The coexistence of radar-sensing and communication systems research has received a surge of interest in recent times to tackle the issue of spectrum inadequacy. Designing an optimized radar waveform for a coexistence scenario has been a challenging task for accomplishing the convergence of radar-sensing and communication functionalities, without degrading the performance at either end. This paper proposes a novel global optimization-based Spatial Branch and Bound (SBnB) approach to optimize the phase coefficients of a Non-Linear Frequency Modulated (NLFM) waveform in a CRCS framework. In addition, the Modified-Power Ratio Constraint-Cramér–Rao Lower Bound (M-PRC-CRLB), a local optimization-based approach is proposed to optimize the phase coefficients of an NLFM waveform. The spectral energy distribution and auto-correlation characteristics of an NLFM waveform are comprehensively investigated for various values of polynomial order (N) and at different threshold Signal-to-Noise-Ratio (SNR) values. To compare the proposed waveform design approaches (M-PRC-CRLB, SBnB) with the existing waveform design approaches namely, Minimum Estimation Error Variance (MEEV) and PRC- CRLB, a Peak-to-Side-Lobe-Ratio (PSLR), and Integrated-Side-Lobe-Ratio (ISLR) are evaluated at various polynomial orders and threshold SNR values. Furthermore, the performance of a CRCS is assessed using the radar estimation rate and communication data rate. The simulation results reveal that the proposed optimized radar waveform design approaches provide improved performance compared to the existing radar waveform design approaches in terms of radar estimation rate. Further, the proposed global optimization-based SBnB approach achieves a comparable performance of the communication data rate. In addition, the proposed approaches accomplish enhanced spectral utilization, controlled side-lobe energy levels, reduced range-domain ambiguities, and a higher information rate in a CRCS.

New Class of Cosine-Sum Windows

Window functions are required to achieve excellent frequency resolution, peak sidelobe ratio, and sidelobe decay. The cosine-sum window function satisfies these requirements. However, conventional cosine-sum windows limit the number of terms and coefficient values. Therefore, this study proposes a new class of cosine-sum windows that has more terms than those in the conventional cosine-sum window and considers positive and negative coefficients. For such windows, we present three design examples. The first is a window function with low sidelobe decay, which reduce the sidelobes by adding correction terms to the conventional windows without damaging the sidelobe decay. The second is a window function that improves the frequency resolution by emphasizing the discontinuities of the extracted signal. The third is a window function that reduces sidelobes further without deteriorating the frequency resolution by adding correction terms to the window functions, which are designed in advance. We confirmed the effectiveness of these examples of the proposed window function.

Joint Subcarrier and Power Allocation for Integrated OFDM Waveform in RadCom Systems

In the integrated radar and communication (RadCom) systems, the integrated orthogonal frequency division modulation (OFDM) waveform with interleaved subcarriers (IS) can simultaneously perform radar and communication functions. However, the autocorrelation function (ACF) of the integrated waveform may have high sidelobe level with high probability due to the discontinuous spectrum for radar. To solve this problem, in this letter, a joint subcarrier and power allocation method is proposed to minimize the peak-to-sidelobe ratio (PSLR) while meeting the requirement of the communication data rate (CDR) and maintaining a certain range resolution. The formulated optimization problem is nonconvex, and we propose the cyclic minimization algorithm to obtain the subcarrier and power allocation. Finally, several numerical results are provided to verify the effectiveness of the proposed method.

Quick Quality Assessment and Radiometric Calibration of C-SAR/01 Satellite Using Flexible Automatic Corner Reflector

C-SAR/01, the successor of China’s Gaofen-3 Satellite, which launched on 23 November 2021, is the first synthetic aperture radar (SAR) satellite to be launched in China’s civil space infrastructure plan and has served as an invaluable data resource. Radiometric calibration and validation are prerequisites for the quantitative application of SAR data. In this study, the radiometric calibration experiments of C-SAR/01 data of the ultra-fine strip (UFS) and fine strip I (FSI) modes were conducted applying flexible automatic triangular trihedral corner reflectors deployed in Xilinhot SAR satellite calibration and validation site. Accordingly, the image quality and radiometric calibration accuracy were evaluated. The results show that the spatial resolution, peak sidelobe ratio, and integrated sidelobe ratio of UFS and FSI mode data of C-SAR/01 are better than those of the design indexes, and the calibration results from the integral method are more stable than those from the peak method. Furthermore, the standard deviation of the calibration constant for UFS mode data is 0.234 dB, with the relative and absolute calibration accuracies obtained as 0.233 and 0.532 dB, respectively, whereas the standard deviation calibration constant for FSI mode data is 0.198 dB, with its relative and absolute calibration accuracies evaluated as 0.199 and 0.333 dB, respectively.

Research on Ultra-Wideband NLFM Waveform Synthesis and Grating Lobe Suppression.

Ultra-wideband (UWB) nonlinear frequency modulation (NLFM) waveforms have the advantages of low sidelobes and high resolution. By extending the frequency domain wideband synthesis method to the NLFM waveform, the synthetic bandwidth will be limited, and the grating lobe will grow as the number of subpulses increases at a fixed synthetic bandwidth. Aiming for the highly periodic grating lobes caused by equally spaced splicing and small subpulse time-bandwidth products (TxBW), a multisubpulse UWB NLFM waveform synthesis method is proposed in this paper. Random frequency hopping and spectral correction are utilized to disperse the energy of periodic grating lobes and optimize the matched filter of the subpulse, thereby reducing notches and Fresnel ripples in the synthesized spectrum. The results of the hardware-in-the-loop simulation experiment show that the peak sidelobe ratio (PSLR) and the integral sidelobe ratio (ISLR) of the NLFM synthetic wideband waveform (SWW) obtained by 50 subpulses with a bandwidth of 36 MHz are improved by 4.8 dBs and 4.5 dBs, respectively, when compared to the frequency domain wideband synthesis method, and that the grating lobe is suppressed by an average of 10.6 dBs. It also performs well in terms of point target resolution, and it has potential for 2D radar super-resolution imaging.

Air target recognition method against ISRJ for radio frequency proximity sensors using chaotic stream encryption

The interrupted-sampling repeater jamming (ISRJ) can cause false targets to the radio-frequency proximity sensors (RFPSs), resulting in a serious decline in the target detection capability of the RFPS. This article proposes a recognition method for RFPSs to identify the false targets caused by ISRJ. The proposed method is realized by assigning a unique identity (ID) to each RFPS, and each ID is a periodically and chaotically encrypted in every pulse period. The processing technique of the received signal is divided into ranging and ID decryption. In the ranging part, a high-resolution range profile (HRRP) can be obtained by performing pulse compression with the binary chaotic sequences. To suppress the noise, the singular value decomposition (SVD) is applied in the preprocessing. Regarding ID decryption, targets and ISRJ can be recognized through the encryption and decryption processes, which are controlled by random keys. An adaptability analysis conducted in terms of the peak-to-side lobe ratio (PSLR) and bit error rate (BER) indicates that the proposed method performs well within a 70-kHz Doppler shift. A simulation and experimental results show that the proposed method achieves extremely stable target and ISRJ recognition accuracies at different signal-to-noise ratios （SNRs） and jamming-to-signal ratios (JSRs).

Photonic-Assisted Generation of Flexible and Switchable Multi-Band Linearly Frequency Modulated Microwave Waveforms

A novel photonic scheme based on parallel dual-drive Mach-Zehnder modulator (DDMZM) to generate flexible and switchable multi-band linearly frequency modulated (LFM) microwave waveforms is proposed. In the scheme, a radio frequency (RF) local oscillator is applied to one arm of DDMZM1 and DDMZM2 with a relative phase of 90°, respectively; while a single-chirp signal to the other arms of the two DDMZMs with a tunable relative phase shift. The generated two independently lightwaves are detected by a balanced photodetector (BPD) and the switchable multi-band LFM signals are generated flexibly. By appropriately adjusting the phase difference <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">θ</i> , dual-band complementary LFM signals and multi-band LFM signals can be easily switched. Based on simulations, the dual-band complementary LFM waveforms centered at 10 GHz and 30 GHz are generated with a doubled bandwidth (3.2 GHz) as <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">θ =</i> 0, the multi-band LFM microwave waveforms with center frequency-bandwidth of 10 GHz-1.6 GHz, 20 GHz-6.4 GHz and 30 GHz-1.6 GHz, covering X, K and Ka bands, are simultaneously obtained with flatness of 1.9 dB as <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">θ</i> = π/2 or 3π/2. Their autocorrelation results manifest high peak-to-sidelobe ratio (PSR) about 14 dB, and good pulse compression capabilities. The presented scheme features its compact structure, easiness in switching control, as well as larger bandwidth, and has potential applications in multifunctional radars.