Inverse Synthetic Aperture Ladar Imaging Research Articles

Moving Real-Target Imaging of a Beam-Broaden ISAL Based on Orthogonal Polarization Receiver and Along-Track Interferometry

In response to the application requirement of wide-range high-resolution imaging of non-cooperative moving real targets by inverse synthetic-aperture ladar (ISAL), experiments were conducted on the depolarization effect of target materials, and the polarization selection of ISAL receiving and transmitting channels was discussed. Considering the impact of target depolarization and the demand for along-track interferometry, combined with beam-broaden and high-gain amplifiers, an ISAL system design method that can stably image multiple non-cooperative real targets has been proposed. Under the condition of broadening the transmitting and receiving beams to 3° in the elevation direction for non-cooperative moving vehicles, echo data with a duration of 1 s is obtained. The spatial correlation algorithm combined with along-track interferometry is used to estimate the vibration phase error. The sub-aperture Range-Doppler algorithm is used for imaging. The ISAL imaging results of the moving vehicle validated the high-resolution imaging ability of ISAL and its potential for stable imaging of non-cooperative moving real targets.

2-D inverse synthetic aperture Ladar imaging and tracking of maneuvering extended Micro-Doppler UAVs in atmospheric turbulence with skewness

The inverse synthetic aperture Ladar (ISAL) is an important system for observation of space objects. Here, a 2-D ISAL imaging and tracking algorithm is proposed for low observable maneuvering extended objects tracking (M−EOT) such as small space UAVs. When imaging maneuvering objects with ISAL, dispersion and Doppler frequency time-variation exist in the range and cross-range echo signal, respectively. Additionally, the ISAL system can achieve high-resolution images for long-range moving objects, while its performance is affected by atmospheric turbulence. Atmospheric turbulence is a very complicated random state formed by the instability of regular laminar flow at a high maneuvering velocity, which is caused by the random motion of the atmosphere and lead to the random fluctuation of the atmospheric refractive index. Therefore, in real-time M−EOT scenario, the measurements distribution over the whole object is not symmetrical but distributed and skewed in some portions while a target maneuvers due to the unbalanced of reflection that caused by the atmospheric turbulence. In practice, the micro Doppler effect caused by micro moving components such as drone rotors will seriously affect the focused ISAL imaging of the M−EOT’s rigid body. To solve these problems in real-time low observable M−EOTs imaging and tracking from 2-D ISAL system, a novel robustness measurement model and recursion multi-Bernoulli track-before-detect filter based on a multiple model skewed non-symmetrically normal distribution is represented with more than one ellipse and lower complexity. In this paper, the Radon-Laplace method is presented to reduce this micro-Doppler effect in ISAL imaging. Additionally, we will eliminate the effect of atmospheric turbulence in ISAL Imaging by using the network-based variance–covariance estimation (NVCE) weighting method. In particular, we describe the M−EOT’s state through the random matrices model (RMM). In RMM, the extent is applied by one ellipse, which often lose information about size, heading, and shape, when the scatter centers are distributed symmetrically around the M−EOT’s centroid. In this paper, a new observation model used to modify a sub-RMM by considering the characteristics of 2-D ISAL data is proposed. Simulation results demonstrates the proposed robustness algorithm with the influence of the atmospheric turbulence and micro-Doppler.

Effects of Atmospheric Coherent Time on Inverse Synthetic Aperture Ladar Imaging through Atmospheric Turbulence

Inverse synthetic aperture ladar (ISAL) can achieve high-resolution images for long-range moving targets, while its performance is affected by atmospheric turbulence. In this paper, the dynamic evolution of atmospheric turbulence is studied by using an infinitely long phase screen (ILPS), and the atmospheric coherent time is defined to describe the variation speed of the phase fluctuation induced by atmospheric turbulence. The simulation results show that the temporal decoherence of the echo induced by turbulence causes phase fluctuation and introduces an extra random phase, which deteriorates the phase stability and makes coherent synthesis impossible. Thus, we evaluated its effects on ISAL imaging and found a method to mitigate the impact of turbulence on ISAL images. The phase compensation algorithm could correct the phase variation in different pulses instead of that within the same pulse. Therefore, the relationship between the atmospheric coherent time and pulse duration time (rather than that between the atmospheric coherent time and ISAL imaging time) ultimately determines the ISAL imaging quality. Furthermore, these adverse effects could be mitigated by increasing the atmospheric coherent time or decreasing the pulse duration time, which results in an improvement in the ISAL imaging quality.

Vibration phases estimation based on orthogonal interferometry of inner view field for ISAL imaging and detection.

Inverse synthetic aperture ladar (ISAL) has the capability to achieve high-resolution imaging of long-distance targets in a short time because of the laser's short wavelength. However, the unexpected phases introduced by target vibration in the echo can cause defocused imaging results of the ISAL. How to estimate the vibration phases has always been one of the difficulties in ISAL imaging. In this paper, in view of the echo's low signal-to-noise ratio, the orthogonal interferometry method based on time-frequency analysis is proposed to estimate and compensate the vibration phases of ISAL. The method can effectively suppress the influence of noise on the interferometric phases and accurately estimate vibration phases using multichannel interferometry in the inner view field. The effectiveness of the proposed method is validated through simulations and experiments, including a 1200m distance cooperative vehicle experiment and a 250m distance noncooperative unmanned aerial vehicle experiment.

Moving target imaging of a dual-channel ISAL with binary phase shift keying signals and large squint angles.

A dual-channel inverse synthetic aperture ladar imaging experimental system based on wide-pulse binary phase coded signals and its moving target imaging are introduced. The analysis, simulation, and experimental data processing results of binary phase coded signal Doppler compensation and pulse compression are included. The method of motion phase error estimation based on interferometric processing and the imaging method with small computation in the case of large squint angles are proposed, and the simulation results are presented. The effectiveness of the imaging method is verified by experimental data processing. Doppler frequency curves are estimated based on time-frequency analysis of echo signals, and the coarse compensation of motion phase error is realized. According to the interferometric phase and coherence coefficient of dual-channel echo signals' time-frequency analysis, the coherence of the dual-channel echo signals is checked, and along-track interferometry can be applied to the precise compensation. The stable interferometric phase and increased coherence coefficient of actual dual-channel data imaging results indicate the effectiveness of the motion phase error compensation method proposed. Considering characteristics of inverse synthetic aperture ladar (ISAL) imaging, after dividing echo signals into multiple sub-apertures, range-Doppler algorithm and sub-aperture stitching are adopted, the stitched image is corrected geometrically through Stolt transformation, and the computation is reduced.

Noise-Robust Vibration Phase Compensation for Satellite ISAL Imaging by Frequency Descent Minimum Entropy Optimization

Inverse synthetic aperture ladar (ISAL) can perform high-resolution imaging for satellites. However, due to the short wavelength of the laser, satellite micro-vibration will introduce space-variant vibration phase error (SVVPE) and space-invariant vibration phase error (SIVVPE) in the echoes, which seriously blur the ISAL image. In this paper, we propose a noise-robust vibration phase compensation algorithm to accurately estimate and correct these two types of vibration phase errors by frequency descent minimum entropy optimization. Firstly, considering the characteristics of the micro-vibration of satellites, we establish a novel phase error model based on the Fourier series theory, which only contains low-frequency vibration components. The estimation of the phase errors is then translated into the estimation of the model’s Fourier coefficients, which can be achieved by a multi-dimensional minimum entropy optimization. After that, a frequency descent method (FD) is proposed to transform the multi-dimensional optimization into a group of two-dimensional optimizations so that the proposed algorithm can achieve monotonic iterative convergence. In addition, we introduce a solution space adaptive reduction operation to reduce the computational burden when solving the two-dimensional minimum entropy optimizations by the genetic algorithm (GA) to obtain the global optimal solution. Finally, experiments based on the simulated data and the real measured data confirm the effectiveness of the proposed algorithm. Compared with the traditional methods, the proposed algorithm achieves higher phase error estimation accuracy and better image quality.

Inverse synthetic aperture ladar imaging based on modified cubic phase function.

Inverse synthetic aperture imaging ladar (ISAL) can achieve high-resolution images, and yet it faces pulse-to-pulse high-order phase errors that the microwave radar can ignore. The high-order phase errors are almost caused by mechanical vibrations in general, which blur the azimuth focusing effect. This paper presents an ISAL imaging model to obtain high-resolution images. A novel modified cubic phase function (CPF) algorithm is proposed to compensate the additional high-order phase errors. Some high-resolution well-focused ISAL simulation images and real target images are shown to validate the methods. It is shown that the third-order phase errors are compensated by the distinctive digital signal process and the image entropy of real target images is reduced significantly.

Multi-Channel Inverse Synthetic Aperture Ladar Imaging Detection Technology and Experimental Research

Multi-Channel Inverse Synthetic Aperture Ladar Imaging Detection Technology and Experimental Research

Feature extraction algorithm of precession target based on image length and Doppler broadening.

In space defense, utilizing the micromotion features to distinguish real targets from interfering targets and decoys is effective. Due to the imaging of the high-speed precession target by microwave radar consisting of isolated scattering centers, there are many difficulties in using inverse synthetic aperture radar (ISAR) images for feature extraction. On the other hand, the inverse synthetic aperture ladar (ISAL) image is relatively continuous because of the short wavelength of laser, and the image sequence contains information about the variation in image length and Doppler width caused by target precession, which can be used for inverse motion parameters. By establishing an observation model of the precession target and performing image processing on the obtained ISAL image at different times, the image length sequence and Doppler width sequence can be obtained. Using the ellipse fitting method to process the obtained sequence, the precession parameters of the target can be obtained. The algorithm does not require prior information such as the radius and speed of the target motion, effectively improving the practicability of the algorithm. Finally, the effectiveness of the algorithm is verified by experimental results, and the error is controlled within 2%.

Extended Target Three-Dimensional Reconstruction From Inverse Synthetic Aperture Ladar Image Sequence

Inverse Synthetic Aperture Ladar (ISAL) can continuously capture images of the target in complex motion, which provides an opportunity for the 3-D reconstruction. However, the existing 3-D imaging methods need to meet some specific conditions, including multiple isolated prominent scattering points in the image, known or parametric motion of the target, and 360° observation of the target. To relax these restrictions, a novel 3-D reconstruction method is proposed. In this method, the corner of the target is first detected and used as a reference point. Then, the positioning accuracy of these fiducial points is greatly improved by the relationship between the radial range and velocity. Finally, the 3-D reconstruction is realized by the singular value decomposition of the measurement matrix. The data obtained from the outdoor experiment are used to test the proposed method. By this process, a series of images of a satellite model which is 2 km away are acquired. The size and shape errors of the reconstruction are less than 10%. The result demonstrates the effectiveness of the 3-D reconstruction method.

An airborne inverse synthetic aperture ladar imaging method based on sparse sampling

The inverse synthetic aperture ladar combines coherent laser technology with synthetic aperture imaging to achieve centimeter-level resolution over a distance of thousands of kilometers. Due to the short wavelength, the required pulse repetition frequency of ladar is very high. Furthermore, because of the uncertain trajectory of the non-cooperative target, the problem of sparse sampling always exists in azimuthal direction. This paper applies inverse synthetic aperture ladar technology into airborne platform, and studies the reconstruction of ladar image under the condition of azimuthal sparse sampling. A frequency spectrum unwrapping method is proposed based on linear observation matrix and Compressed Sensing theory, to restore the image from sparsely sampled echo. Simulation results demonstrate the effectiveness of proposed method.

Inverse synthetic aperture ladar imaging algorithm for space spinning targets

Due to the limitation of laser modulation technology, the azimuth Doppler ambiguity problem exists in the process of inverse synthetic aperture ladar (ISAL) imaging for spinning targets. The traditional azimuth imaging method will not be used to obtain a good two-dimensional image. Therefore, we consider using the target's spinning information for imaging. The spatial geometric model of the spinning target ISAL imaging is established, and the characteristics of the echo signal are analysed. An ISAL imaging algorithm based on the backward projection transform is proposed. First, the spinning angular velocity of the target is obtained by the generalised autocorrelation method, and then the envelope and phase of the distance and the slow time domain are transformed into a backward projection to achieve coherent accumulation, and the two-dimensional high-resolution image of the spinning target is finally obtained. Due to the use of echo phase information, the sidelobe effect is low and the resolution is high. The simulation results show that the algorithm can still get well-focused images under low SNR and Doppler ambiguity.

Novel Scaling Approach for ISAL via the Fractional Fourier Transform

Inverse Synthetic Aperture LADAR (ISAL) can obtain high resolution images of remote targets. In order to measure the dimension of the target, the ISAL image must be scaled. Many existing scaling methods require isolated strong scattering centers which are not easily found in ISAL images. To solve this problem, a novel ISAL scaling method is proposed. The method estimates the Doppler frequency modulation rate of each range row by the fractional Fourier transform (FrFT) and image entropy. The linear relationship between the frequency modulation rate and the range is used to obtain an estimate of the target equivalent rotational angular velocity which is the key parameter for scaling. The outfield experimental results confirm the effectiveness of the method.

3-D Inverse Synthetic Aperture Ladar Imaging and Scaling of Space Debris Based on the Fractional Fourier Transform

The inverse synthetic aperture ladar (ISAL) is an important method for observation and imaging of space targets. Here, a 3-D ISAL imaging algorithm is proposed for spinning targets such as space debris. Since laser wavelength is 4–5 orders of magnitude smaller than that of microwave, the Doppler frequency caused by target motion is more pronounced in ISAL. Doppler frequency modulation rates can be estimated by the fractional Fourier transform with respect to azimuth slow time even when the rotation angle is small such that scattering centers do not migrate through a range cell. Then, slant range, Doppler frequency, and Doppler frequency modulation rates form a 3-D space. The angular velocity and the incident angle can be estimated by the position relationship between the scattering centers in two observations. After image scaling, the 3-D shape and size of the target can be obtained. The 3-D structure of the target in the simulation experiment is accurately reconstructed. Monte Carlo experiments are conducted to discuss the effect of the signal-to-noise ratio and observation time on the algorithm. Finally, the effectiveness and robustness of the algorithm are verified.

An Inverse Synthetic Aperture Ladar Imaging Algorithm of Maneuvering Target Based on Integral Cubic Phase Function-Fractional Fourier Transform

When imaging maneuvering targets with inverse synthetic aperture ladar (ISAL), dispersion and Doppler frequency time-variation exist in the range and cross-range echo signal, respectively. To solve this problem, an ISAL imaging algorithm based on integral cubic phase function-fractional Fourier transform (ICPF-FRFT) is proposed in this paper. The accurate ISAL echo signal model is established for a space maneuvering target that quickly approximates the uniform acceleration motion. On this basis, the chirp rate of the echo signal is quickly estimated by using the ICPF algorithm, which uses the non-uniform fast Fourier transform (NUFFT) method for fast calculations. At the best rotation angle, the range compression is realized by FRFT and the range dispersion is eliminated. After motion compensation, separation imaging of strong and weak scattering points is realized by using ICPF-FRFT and CLEAN technique and the azimuth defocusing problem is solved. The effectiveness of the proposed method is verified by a simulation experiment of an aircraft scattering point model and real data.

Vibration phases estimation based on multi-channel interferometry for ISAL.

Target vibration introduces unexpected vibration phases in the echo signal of inverse synthetic aperture LADAR (ISAL). The vibration phases cause the imaging results to be defocused. How to estimate the vibration phases has always been one of the difficulties in ISAL imaging, and there has not been an effective solution. In this paper, two methods are proposed to estimate the vibration phases in different situations. The method based on multi-channel along-track interferometry (MCATI method) is for some cases that the target velocity vector is parallel to some baselines of ISAL. The method based on orthogonal interferometry (OI method) is for other cases that the target velocity vector is not parallel to any baseline of ISAL. In addition, a high signal to noise ratio (SNR) is essential for the MCATI and OI methods to get high estimation accuracy. Therefore, a large power-aperture product should be carefully considered in the ISAL system design. Furthermore, on the condition of low SNR, range cell accumulation is also helpful to reduce the influence of noise. Take the ISAL, which is utilized to image the satellite in 500km orbit, as an example, the estimation accuracy can satisfy the demand of synthetic aperture imaging with 0dB single-pulse SNR and 300 range cell accumulation. The proposed methods are verified with simulation and experiment.

Inverse synthetic aperture LADAR demonstration: system structure, imaging processing, and experiment result.

A long-distance inverse synthetic aperture LADAR (ISAL) imaging experiment outdoors over 1km for cooperative targets is demonstrated, which gets a two-dimensional high-resolution image with resolution exceeding 2.5cm. The system utilizes an electro-optic in-phase and quadrature modulator to output a linear frequency-modulated continuous waveform (LFMCW) with a bandwidth of 6GHz and pulse repetition frequency (PRF) of 16.7KHz. For the problem of the coherence of the laser, the effects of the coherent processing interval (CPI) and time delay of the local oscillator (LO) on the coherence are discussed. The fiber delay line is set and the CPI is reduced to lower the requirement of the frequency stability of the laser source. The images are formed by two-dimensional Fourier transform and joint time-frequency transform methods, respectively. In this paper, we present the system structure, imaging processing, and the experiment result in detail. The experiment result validates the performance of our system for ISAL imaging.

机动目标逆合成孔径激光雷达成像算法

机动目标逆合成孔径激光雷达成像算法

Inverse synthetic aperture ladar imaging with stepped‐frequency continuous waveform

Inverse synthetic aperture ladar (ISAL) is analogous to the inverse synthetic aperture radar but works at frequency 104–5 times higher. A method is proposed to process the ISAL data with stepped-frequency continuous waveform (SFCW). Due to the short wavelength used for ISAL and the relatively long transmission of the SFCW, the motion during the transmission and the relative range shift between adjacent sub-band chirps must be both taken into account while performing the bandwidth synthesis and imaging. An analytic signal model was derived to address this problem. In the proposed model, three additional terms, named the bulk range walk term, the stepped phase error term and the additional range shift, were formulated in ISAL imaging with SFCW for the first time. Based on the signal model, an effective method was proposed to coherently synthesise all the sub-band echoes and then focus the ISAL image. Experimental result was shown and the focused image of an airplane model demonstrated the effectiveness of the proposed method.

Inverse Synthetic Aperture Ladar Imaging Algorithm for Maneuvering Target Based on FRFT-CLEAN

Inverse Synthetic Aperture Ladar Imaging Algorithm for Maneuvering Target Based on FRFT-CLEAN