Range Walk Research Articles

Long-Time Coherent Integration Method for Passive Bistatic Radar Using Frequency Hopping Signals.

Long-time coherent integration using frequency hopping signals is a challenging problem for passive bistatic radar due to its frequency hopping characteristics. Apart from range walk, range curve, and Doppler frequency migration, Doppler diffusion caused by frequency hopping characteristics occurs within the observation time, which also lowers the detection performance. To deal with this problem, a novel coherent integration method for frequency hopping signals based on passive bistatic radar is proposed in this paper. In this novel method, range curve and range walk are eliminated by applying generalized Keystone transform. Then, Doppler frequency migration caused by the target's acceleration is compensated for by a parameter search with a designed search scope. Finally, Doppler frequency migration caused by frequency hopping characteristics is compensated for by designing a new acceleration compensation function and a revised rotation factor for Fourier transform. Since migration effects caused by frequency hopping characteristics are considered and compensated for when using frequency hopping signals, the weak target echo can be better integrated in the observation time compared to when using the existing methods. The simulation results and performance analysis illustrate the effectiveness of the proposed method.

A Modified Frequency Nonlinear Chirp Scaling Algorithm for High-Speed High-Squint Synthetic Aperture Radar with Curved Trajectory

The imaging of high-speed high-squint synthetic aperture radar (HSHS-SAR), which is mounted on maneuvering platforms with curved trajectory, is a challenging task due to the existence of 3-D acceleration and the azimuth spatial variability of range migration and Doppler parameters. Although existing imaging algorithms based on linear range walk correction (LRWC) and nonlinear chirp scaling (NCS) can reduce the range–azimuth coupling of the frequency spectrum (FS) and the spatial variability of the Doppler parameter to some extent, they become invalid as the squint angle, speed, and resolution increase. Additionally, most of them ignore the effect of acceleration phase calibration (APC) on NCS, which should not be neglected as resolution increases. For these issues, a modified frequency nonlinear chirp scaling (MFNCS) algorithm is proposed in this paper. The proposed MFNCS algorithm mainly includes the following aspects. First, a more accurate approximation of range model (MAARM) is established to improve the accuracy of the instantaneous slant range history. Second, a preprocessing of the proposed algorithm based on the first range compression, LRWC, and a spatial-invariant APC (SIVAPC) is implemented to eliminate most of the effects of high-squint angle and 3-D acceleration on the FS. Third, a spatial-variant APC (SVAPC) is performed to remove azimuth spatial variability introduced by 3-D acceleration, and the range focusing is accomplished by the bulk range cell migration correction (BRCMC) and extended secondary range compression (ESRC). Fourth, the azimuth-dependent characteristics evaluation based on LRWC, SIVAPC, and SVAPC is completed to derive the MFNCS algorithm with fifth-order chirp scaling function for azimuth compression. Consequently, the final image is focused on the range time and azimuth frequency domain. The experimental simulation results verify the effectiveness of the proposed algorithm. With a curved trajectory, HSHS-SAR imaging is carried out at a 50° geometric squint angle and 500 m × 500 m imaging width. The integrated sidelobe ratio and peak sidelobe ratio of the point targets at the scenario edges approach the theoretical values, and the range-azimuth resolution is 1.5 m × 3.0 m.

Long-Term Coherent Integration Algorithm for High-Speed Target Detection.

Long-term coherent integration (CI) can effectively improve the radar detection capability for high-speed targets. However, the range walk (RW) effect caused by high-speed motion significantly degrades the detection performance. To improve detection performance, this study proposes an improved algorithm based on the modified Radon inverse Fourier transform (denoted as IMRIFT). The proposed algorithm uses parameter searching for velocity estimation, designs a compensation function based on the relationship between velocity and distance walk and Doppler ambiguity terms, and performs CI based on the compensated signal. IMRIFT can achieve RW correction, avoid the blind-speed sidelobe (BSSL) effect caused by velocity mismatch, and improve detection performance, while ensuring low computational complexity. In addition, considering the relationship between energy concentration regions and bandwidth in the 2D frequency domain, a fast method based on IMIRFT is proposed, which can balance computational cost and detection capacity. Finally, a series of comparative experiments are conducted to demonstrate the effectiveness of the proposed algorithm and the fast method.

Moving Target Detection Algorithm for Millimeter Wave Radar Based on Keystone-2DFFT

Millimeter wave radar has the advantage of all-day and all-weather capability for detection, speed measurement. It plays an important role in urban traffic flow monitoring and traffic safety monitoring. The conventional 2-dimensional Fast Fourier Transform (2DFFT) algorithm is performed target detection in the range-Doppler domain. However, the target motion will induce the range walk phenomenon, which leads to a decrease in the target energy and the performance of the target detection and speed measurement. To solve the above problems, this paper proposes a moving vehicle detection algorithm based on Keystone-2DFFT for a traffic scene. Firstly, this paper constructs and analyzes the Frequency Modulated ContinuousWave (FMCW) moving target signal model under traffic monitoring scenario’s radar observation geometry. The traditional 2DFFT moving target detection algorithm is briefly introduced. Then, based on mentioned signal model, an improved moving vehicle detection algorithm based on Keystone-2DFFT transform is proposed. The method first input the echo, then the range walk is removed by keystone transformation. the keystone transformation is achieved via Sinc interpolation. Next is transform data into range-Doppler domain to perform detection and speed estimation. The algorithm is verified by simulation data and real data.

Radar fast long-time coherent integration via TR-SKT and robust sparse FRFT

Long-time coherent integration (LTCI) is an effective way for radar maneuvering target detection, but it faces the problem of a large number of search parameters and large amount of calculation. Realizing the simultaneous compensation of the range and Doppler migrations in complex clutter background, and at the same time improving the calculation efficiency has become an urgent problem to be solved. The sparse transformation theory is introduced to LTCI in this paper, and a non-parametric searching sparse LTCI (SLTCI) based maneuvering target detection method is proposed. This method performs time reversal (TR) and second-order Keystone transform (SKT) in the range frequency & slow-time data to complete high-order range walk compensation, and achieves the coherent integration of maneuvering target across range and Doppler units via the robust sparse fractional Fourier transform (RSFRFT). It can compensate for the nonlinear range migration caused by highorder motion. S-band and X-band radar data measured in sea clutter background are used to verify the detection performance of the proposed method, which can achieve better detection performance of maneuvering targets with less computational burden compared with several popular integration methods.

A Modified Range Doppler Algorithm for High-Squint SAR Data Imaging

The high-squint airborne Synthetic Aperture Radar (SAR) has the ability to detect the target area flexibly, and the detection swath is significantly increased compared with the side-looking SAR system. Therefore, it is of great significance to carry out research on high-precision imaging methods for high-squint airborne SAR. However, the high-squint SAR echoes have large Range Cell Migration (RCM), resulting in severe range–azimuth coupling and strong spatial variation. In this paper, a Modified Range Doppler Algorithm (MRDA) is proposed to cope with these effects introduced by the significant RCM in high-squint airborne SAR imaging. The bulk compensation preprocessing is first adopted to remove the considerable RCM and severe cross-coupling in a two-dimensional frequency domain. Then, Non-Linear Chirp Scaling (NLCS) in the range direction is utilized to equalize the range-variant chirp rate caused by the residual RCM and coupling and, therefore, the consistent range phase compensation can be fulfilled in range frequency domain. The modified correlation processing is executed to compensate the residual Doppler phase modulation, the residual RCM and the range-variant cubic phase modulation, which guarantees the characteristics of high efficiency and high precision. The simulations have demonstrated that the MRDA can focus the SAR echoes with large squint angles more effectively than the algorithms based on the Linear Range Walk Correction (LRWC) method.

Sentinel-6 MF Poseidon-4 radar altimeter: Main scientific results from S6PP LRM and UF-SAR chains in the first year of the mission

Poseidon-4 is a dual-frequency redundant radar altimeter on board the European Commission Copernicus Programme Sentinel-6 Michael Freilich satellite, that represents a significant breakthrough with respect to its predecessors Jason-class altimeters due to its digital architecture and to its innovative measurements and calibration modes.In the framework of the Sentinel-6 Michael Freilich commissioning preparatory activities, CNES has contracted CLS for the development of a Sentinel-6 Processing Prototype (S6PP) application. S6PP is a multi-chain processing suite able to process Sentinel-6 Level-1A and Level-1B data products up to Level-2. The novel algorithms developed in the CNES/CLS research and development activities are implemented within S6PP and validated to support the different thematic applications (in particular inland water and ocean) and in view of promoting them for possible implementation in the operational ground segment.The present work covers in particular the main results over open ocean for the main altimetric geophysical variables over the sea surface (sea surface height anomaly, significant wave-height, sigma-nought and wind speed) derived by the Low-Resolution Mode (LRM) and High-Resolution Mode (HRM) chains of S6PP in terms of precision, accuracy, spectral content and measurement stability.Given the reported variation of the payload in-orbit temperatures along with the reported instrumental ageing, and given the tight requirement to measure the GMSL (Global Mean Sea Level) in seamless continuity with Jason-3, the clear goal for S6PP was to process the S6-MF data with the minimum possible level of approximations along the processing pipeline but still maintaining a very efficient prototype from the computational point of view.For this scope, a novel and computationally efficient numerical retracking scheme with interface to the in-flight PTR (Point Target Response) provided by the instrument calibration chain has been put in place within S6PP for both the Low-Resolution and High-Resolution modes whereas the Delay-Doppler beam-forming is carried out by applying the range walk correction based on a computationally efficient algorithm (Chirp Zeta-Transform).The impact of the range walk correction and of the in-flight PTR interface is assessed for HRM and LRM, respectively.The paper shows that the proposed processing baseline ensures a dataset robust from the currently known instrumental degradation or ageing issues, both in LRM and HRM mode and, once this is done, that Sentinel-6 Michael Freilich global mean sea level measurement is in line with the one measured by Jason-3.

Bayesian Detectors for Wideband Radar Target With Range Walking in Compound Gaussian Clutter

In this paper, the problem of the wideband radar target detection with the range walking in compound Gaussian clutter without the secondary data is addressed. The wideband radar target return with the range walking is represented as a canonical linear model in the multi-rank subspace, and the clutter is modeled as a two-dimensional random process with separable complex inverse Wishart distributed random covariance matrices in the pulse and range-frequency domains. The generalized likelihood ratio test (GLRT), the Wald test and the Rao test based on the above target and clutter models are designed under the Bayesian framework. The Laplace approximation is adopted to compute the second-kind confluent hypergeometric function of matrix argument (SKCHFMA) in the proposed detectors. Finally, the performance of the detectors is validated by the simulations.

Method of 2-D Range-Doppler Imaging for Plasma Wake Based on Range Walk Correction

When a hypersonic vehicle flies in the atmosphere, plasma sheath and trails are configured around the vehicle due to aerodynamic heating and ablation, which distort the radar echo signal and then influence the target range information and Doppler frequency extracted from the echoes. In order to examine the impact of plasma laminar wake on radar detection, this article is primarily aimed to establish a laminar wake echo model based on a linear frequency-modulated continuous wave (LFMCW) radar, which takes into account the reaction control system of laminar wake by employing the Born approximation solution and the characteristics of the inhomogeneous and nonunique velocity of the wake medium. An echo signal processing method is also developed, in which the stretch processing technique is combined with the keystone transform of the target range walk correction. Such a treatment not only reduces the sampling rate and bandwidth, but also eliminates the cross-range cells phenomenon caused by hypersonic; finally, the range-Doppler (RD) image of the wake is achieved by 2-D fast Fourier transform (2-D FFT) processing, and radar range and velocity measurement results in the presence of plasma are obtained.

Decimation keystone algorithm for forward-looking monopulse imaging on platforms with uniformly accelerated motion

Forward-looking imaging for maneuvering platforms has garnered significant interest in many military and civilian fields. As the maneuvering trajectory in the scanning period can be simplified as the constant acceleration maneuver, monopulse imaging is applied to enhance the azimuthal resolution of the forward-looking image. However, the maneuver causes severe range migration and Doppler shift; this often results in range location error due to the space-varying Doppler shifts and the failure of angle estimation. We propose a decimation keystone algorithm based on the chirp-Z transform (CZT). First, the pulse repetition frequency (PRF) is decimated with an integer; thus, the azimuthal sampling sequence is decimated into many sub-sequences. Then, the linear range walk correction (LRWC) is performed on each sub-sequence using the keystone transform, significantly reducing the influence of the change of Doppler-ambiguity-number on range location. Further, the sub-sequences are regrouped as one sequence, and the range curvature due to the acceleration is compensated in the frequency domain. Finally, the varying Doppler centroid in each coherent processing interval (CPI) is analyzed and compensated for the sum-difference angular measurements. Simulation results demonstrate the effectiveness of the proposed algorithm for forward-looking imaging under constant acceleration maneuvers and the feasibility of range location error correction.

Signal Accumulation Method for High-Speed Maneuvering Target Detection Using Airborne Coherent MIMO Radar

The airborne coherent multi-input multi-output (MIMO) radar benefiting from coherent integration (including intra-channel integration and inter-channel integration) of multi-channel echoes can obtain superior detection performance for high-speed maneuvering targets. However, due to the coupling motion characteristic between multiple airborne platforms and high-speed targets, the range walk (RW) and Doppler walk (DW) will occur within the intra-channel integration. Besides, the inter-channel signals also exist envelope and phase differences, which will lead to the difficulty in multi-channel integration. We make contributions towards addressing these limitations. On the one hand, we establish a three-dimensional (3-D) geometrical model for high-speed maneuvering target detection with airborne coherent MIMO radar and derive the mathematical expression of radar echoes, while the generalized Radon-Fourier transform (GRFT) is utilized to simultaneously correct the RW and DW for acquiring intra-channel integration. On the other hand, we analyze the properties of GRFT outputs and propose a GRFT-domain integration method to achieve the multi-channel coherent integration. More specifically, the proposed method first constructs a set of coupling equations for the estimation of target motion parameters (i.e., position, velocity and acceleration), then, the target's motion parameters can be estimated by Newton-Raphson method and solving the linear equations. Second, in order to settle the envelope and phase differences between multi-channel echoes, the envelope alignment and phase compensation functions of inter-channel echoes are constituted based on the estimated parameters. Finally, the coherent accumulation of multi-channel echoes can be implemented. Numerical simulations demonstrate the effectiveness of the proposed method.

Translational-Invariant Ultrahigh-Resolution Spaceborne Bistatic SAR Focusing and Image Coordinate Analysis Using Bistatic Polynomial Model

We have proposed a novel process flow for translational-invariant (TI) and ultrahigh-resolution (UHR) bistatic synthetic aperture radar (BSAR) operations, wherein a UHR BSAR image is obtained via coherent integration of sub-aperture images, and its two-dimensional (2D) coordinates are then interpreted. The main contributions of the proposed method are as follows. First, to address additional aliasing of the TI BSAR spectrum after sub-aperture division, linear range walk compensation and its restoration are subsequently performed. This efficiently extends the duration of the Doppler domain after sub-aperture division, accommodating the skewed shape of the TI BSAR spectrum. Second, spatial-variant focusing is achieved via the bistatic polynomial omega-K algorithm (BP-OKA), for which a key consideration is highlighted to perform BP-OKA in the sub-image integration process. In its absence, the same scatterers appeared at different positions in each sub-aperture image, causing failure of coherent accumulation. Finally, to retrieve the range–azimuth coordinates of targets within an illuminated scene, we established a high-order equation using bistatic polynomials, and the 2D image coordinates of targets were determined by solving the equation. This new concept is fully compatible with the proposed BP-OKA and can be used in various spaceborne TI BSAR scenarios. All these contributions were verified using numerical simulations. Accordingly, the proposed processing flow can provide focused SAR images with accurate image coordinate interpretations for TI and UHR BSAR operations.

An Extended Frequency Scaling Algorithm for Bistatic SAR With High Squint Angle

Bistatic synthetic aperture radar (BiSAR) is an extended and complementary observation method to conventional monostatic SAR remote sensing. When high range and azimuth resolution are required in BiSAR, the transmitting platform, i.e., the LEO satellite, should work in the spotlight or sliding spotlight mode, which means a wide bandwidth Chirp signal is transmitted, and the targets are illuminated for a long enough time as well. In order to reduce the sampling frequency in the receiving system and improve the efficiency of the focusing procedure for this BiSAR configuration, the echoes should be dechirp received. A bistatic extended frequency scaling algorithm (Bi-EFSA) is proposed in this paper to deal with the dechirp received bistatic SAR echoes. The first step of Bi-EFSA is the range walk correction in the 2-D time domain, which reduces the space variance of the range curvatures and removals the serious coupling between range and azimuth caused by the high squint angle. After that, the range compression is achieved by secondary range compression (SRC) and bulk shift. Then, the space variance of the azimuth frequency modulation rate, introduced by the range walk correction step, is corrected by implementing the azimuth nonlinear chirp scaling (ANCS) operation. Following this, the focused results in the range frequency and azimuth time domain are obtained by the azimuth compression. The point targets and extended-scene simulations validate the effectiveness of the proposed algorithm.

Multi-channel track-before-detect approach for airborne target with OTH radar

It is a common requirement for over-the-horizon (OTH) radar to detect the sea and airborne targets in the same direction simultaneously. The long coherent integration time (CIT) is needed to detect the sea target and the weak moving target such as aircraft. However, the range walk effect (RWE) will occur within the long integration time, leading to a serious degradation of the airborne target detection and tracking. To settle this problem, a new approach based on the multi-channel track-before-detect (MC-TBD) is proposed in this paper. More specifically, to improve the detection performance of the airborne target with unknown speed, multiple processing channels corresponding to different speed ranges are set under the MC-TBD framework. The received data are processed in each channel in parallel. In each channel, the constraints of the speed range are utilized to determine the number of pulses in the CIT of the airborne target. Then, coherent and noncoherent integration processing are performed sequentially based on the moving target detection (MTD) and track-before-detect (TBD). Finally, the detection results and trajectories of all channels are fused to achieve the final detection and tracking of the airborne target. Simulation results show the superiority of the proposed MC-TBD approach over the existing methods in terms of the performance of detection and tracking for airborne target with OTH radar under the background of simultaneous detection of airborne and sea targets in the same direction.

Modified RD algorithm of highly squint SAR imaging based on range walk removal

In highly squint SAR imaging mode, linear range walk (LRW) plays a leading role in range cell migration (RCM), which is much larger than range bending. Based on the geometric model of highly squint SAR imaging, the characteristics of highly squint SAR echoes are analyzed in this paper. And a modified range-Doppler (RD) algorithm is derived, which is suitable for highly squint mode. The algorithm expands the slant distance to the cubic term, correct linear range walk in the time domain, and correct the range bending in the frequency domain. The simulation results of the point targets verify the feasibility of the algorithm. By comparing with the algorithm before the improvement, the effectiveness of the proposed algorithm is proved.

Chaos single photon LIDAR and the ranging performance analysis based on Monte Carlo simulation.

With the advent of serial production lidars, single photon lidar faces an increasingly severe threat of crosstalk. In this paper, we first propose the concept of Chaos Single Photon (CSP) lidar and establish the theoretical model. In CSP lidar system, chaos laser replaces pulsed laser, and the physical random sequence generated by a Geiger mode avalanche photodiode (GM-APD) responding to chaos laser substitutes the traditional pseudo-random sequence. The mean density of '1' code of the CSP lidar system can exceed 10 million counts per second (Mcps) with a dead time immunity. The theoretical models of detection probability and false alarm rate are derived and demonstrated based on Poisson distribution. The bit error rate (BER) is introduced into the CSP lidar system for evaluating the range walk error intuitively. Additionally, the simulation results indicate that the CSP lidar system has a robust anti-crosstalk capability. Compared with the traditional pseudo-random single photon (PRSP) lidar system, the CSP lidar system not only overcomes range ambiguity but also has a signal to noise rate (SNR) of 60 times, reaching 10000 when the mean echo photoelectron number is 10 per nanosecond. Benefited from large-scale arrays and extremely high sensitivity properties of GM-APDs, we are looking forward to the applications of the CSP lidar in weak signal detection, remote mapping, autonomous driving, etc.

Detection of the near-field targets by non-coaxial underwater single-photon counting lidar

The strong backscattering of near-field water severely limits the detection ability of the coaxial single-photon counting lidar, especially when the target signal peak overlaps with the background(water) signal peak. Based on the important influence of scattering angle on the distribution of echo photons in the volume scattering function (VSF) of water and the BRDF model of target, a detection efficiency model of non-coaxial underwater single-photon counting lidar is established in this paper. It reveals that when the water attenuation coefficient is a fixed value, the maximum detection efficiency and range walk error (RWE) decrease exponentially with the increase of target distance. The variation of the center distance of the transceiver system has the best detection efficiency, which has little effect on the RWE. Compared with the coaxial system, the target detection efficiency of the non-coaxial underwater single-photon counting lidar remains unchanged while suppressing the strong backscattering of near-field water. Monte Carlo simulation results show that the non-coaxial system has faster searching ability for target signals with high attenuation coefficient and overlapping echo peaks. This research lays a theoretical foundation for the fast target search of single-photon counting lidar in complex underwater environment.

Super‐resolution forward‐looking imaging method for manoeuvering platform with optimised dictionary and extended sparsity adaptive matching pursuit

In forward-looking imaging, left-right Doppler is ambiguous and cross-range resolution is limited by real aperture, which result in traditional synthetic aperture radar imaging methods no longer applicable. Besides, the impact of three-dimensional acceleration on an over-complete dictionary matrix and sparse reconstruction kernel is not considered in conventional super-resolution forward-looking imaging methods. To solve these problems, a super-resolution forward-looking imaging method for manoeuvering platforms is proposed. First, the range walk caused by forward-looking geometry and higher-order phase introduced by three-dimensional acceleration are eliminated by compensating a pre-processing function. Subsequently, according to beam steering-based geometry and linear regression model, the over-complete dictionary matrix is optimised to more accurately describe the complicated forward-looking geometry with curved trajectory. Finally, sparsity adaptive matching pursuit kernel with an improved halting condition is adopted to reconstruct the forward-looking scene. The proposed method is supported by point target simulation and surface target simulation.

Motion parameter estimation of high‐speed manoeuvering targets based on hybrid integration and synchrosqueezing transform

In this study, we address the problem of estimating the motion parameters of multiple high-speed manoeuvering targets under low signal-to-noise ratio (SNR) environment with a low-range resolution radar, where the target movement could cause the echo signal energy seriously spread across both the range and Doppler frequency coordinates, and the returned signals from different targets would merge into each other. Based on the subaperture feature enhancement, Hough transform (HT) and the second-order short-time Fourier-based synchrosqueezing transform (FSST2), a novel method, named as EHFSST2, is proposed. The proposed method can robustly extract the targets of interest from environment and accurately estimate the targets' motion parameters. Thanks to its ability to compensate the effects of the range walk, curvature, and the Doppler ambiguity, spreading, wrapping, and the energy of echo signal can be coherently integrated along the target's individual moving trajectory. In addition, several numerical experiments are provided to demonstrate the effectiveness. The results show that the proposed method is superior to some existing methods in terms of the anti-noise ability, measurement accuracy and integration performance.

A Novel High-Squint Spotlight SAR Raw Data Simulation Scheme in 2-D Frequency Domain

Raw data simulation is the front-end work of synthetic aperture radar (SAR), which is of great significance. For high-squint spotlight SAR, the frequency domain simulation algorithm is invalid because of the range-azimuth coupling effect. In order to realize high-squint spotlight SAR raw data simulation in the frequency domain, an algorithm based on coordinate transformation and non-uniform fast Fourier transform (NUFFT) is proposed. This algorithm generates broadside raw data using a two-dimensional (2-D) frequency simulation algorithm; then, coordinate transformation is used by analyzing the characteristics of broadside and high-squint spotlight SAR. After coordinate transformation, NUFFT is carried out to realize the coupling relation in the 2-D frequency domain. Since the coordinate transformation ignores the influence of range walk, the range walk is compensated after NUFFT. As a result, compared with the traditional squint spotlight SAR frequency domain simulation algorithm, the proposed algorithm can improve the accuracy of point and distributed target imaging results, and the efficiency of the proposed algorithm can be significantly improved in contrast the traditional time domain algorithm.