This paper studies the online management of the computational resources between multiple edge clouds to minimize the operational cost for a vehicle-to-network (V2N) service provider, subject to stochastic trajectories of vehicles, the quality-of-service (QoS) and the resource limit. Due to the random mobility of vehicles, it poses challenges in real-time migration management when the computational capacity of each edge cloud and the stringent delay requirement of V2N services are both constrained, resulting in strong temporal-spatial coupling of the migration decisions. The problem could even be intractable to solve as the number of vehicles grows. To tackle these issues, we first propose a multi-layered cloud framework to gather and coordinate migration information between vehicles. Then, a multiagent rollout with feasibility construction approach is developed, where the migration decision can be optimized sequentially for each vehicle based on the coordinated migration information from the central cloud. To handle the potentially infeasible solutions caused by the computational resource constraint, we propose a heuristic method to determine the migration priority at each overloading edge cloud, and an integer program is constructed that can be easily solved to produce feasible solutions. The numerical results show the efficiency of the proposed approach in both economical performance and computational complexity compared to the benchmarks.

In the energy internet era, distributed energy storage systems will be widely used in various industrial, commercial, and residential scenarios. However, the modeling of energy flow and the digital flow of information operate on different temporal and spatial scales in traditional energy storage systems, lacking deep integration between energy flow and information flow. This prevents it from completely addressing the complex battery cell balancing and low safety issues in current distributed energy storage systems. The proposal of software-defined energy storage provides a new approach to solve the inherent problems in the battery industry by introducing the idea of internet shielding terminal differences into energy storage system. We proposed a software-defined reconfiguration battery system (SRBS) in this paper, which can manage different types of energy storage media to adapt to varying loads and operating conditions. Energy-type batteries, power-type batteries, and supercapacitors are integrated together to form an efficient and safe energy storage and power supply system. The hardware architecture and software control method of SRBS are described in detail. Finally, a real-world prototype is charged and discharged to show the successful coexistence and operation of different energy storage media within a single system.

This article presents a new simulator able to generate raw data for ocean wave radar spectrometer (OWRS). Data simulation involves three key procedures: generating 2-D sea wave height, velocity, and acceleration fields by use of a prescribed ocean wave height spectrum; calculating the 2-D sea surface normalized radar cross section (NRCS) field using a quasi-specular backscatter model; and incorporating the generated sea wave height, velocity, and acceleration fields into the radar instantaneous range equation (IRE). Our simulator’s reliability in replicating real-world ocean wave spectra has been confirmed by comparing retrieved wave spectra from simulated OWRS raw data with input reference wave spectra and real-measured radar data. The proposed simulator has several advantages over conventional simulators. Notably, OWRS data generated by the proposed simulator are complex in-phase/quadrature-phase (I/Q) raw data, instead of backscattered power modulation data as simulated by conventional simulators. Our simulator’s other advantages include its ability to reflect the effect of Doppler modulation induced by the motions of the radar platform and the sea waves in the speckle noise spectrum after processing OWRS raw data simulated by the proposed simulator, as well as its ability to embody the effect of range modulation caused by the sea surface topography, including both linear and higher order range modulation effects, in retrieved wave slope spectra. Our simulator offers a powerful tool for understanding complicated interactions between ocean wave dynamics and radar signals. Furthermore, it also provides radar engineers with a cost-effective way to evaluate potential designs for future spaceborne OWRS.

The total mean square slope (mss) of large-scale (in comparison with the scale of radar wavelengths) ocean waves can describe the roughness of the ocean surface. This important parameter has found many applications and can be determined by the dependence of large-scale mss on azimuthal angles. The Surface Waves Investigation and Monitoring instrument onboard the China France Oceanography Satellite (CFOSAT) can provide a two-dimensional (2D) normalized backscattering radar cross section (NRCS) for 2D global ocean-surface wave detection. In this paper, the 2D NRCS is used to calculate the total large-scale mss via two methods. The first method is constructed from regression, while the second scheme is derived from a three-solution method. Finally, the total large-scale mss are calculated using these methods, and the map of the distribution of the global total mss is presented for the first time. Our results show that the two sources of total large-scale mss obtained are consistent with each other. CFOSAT can provide a 2D total large-scale mss map and be used as a new data resource for global applications.

Sea surface winds derived from the spaceborne rotating pencil-beam scatterometers, such as the current Chinese Haiyang-2 (HY-2) scatterometers and the Indian SCATSAT-1 scatterometer, are used in a wide range of atmospheric and oceanic applications. One key problem of the pencil-beam scatterometers is the relatively low wind quality in the nadir region, due to the poor azimuth diversity of the nadir-track observations. This article proposes to include the altimeter backscatter measurements in the wind inversion to improve the retrieved wind quality in the nadir region of HY-2B scatterometer (HSCAT). First, empirical model functions are developed to relate the C- and Ku-band altimeter backscatters to the neutral surface winds at 10-m height. Subsequently, the maximum likelihood estimator, which is commonly used to perform wind inversion for satellite scatterometers, is adapted to retrieve winds with simultaneous scatterometer and altimeter measurements. The significance of altimeter measurements in the combined wind inversion is addressed by comparing the cost functions of the combined scatterometer/altimeter wind retrieval and the nominal scatterometer inversion. The experimental results are eventually validated using moored buoy winds and the European Centre for Medium-range Weather Forecasting (ECMWF) model winds, indicating that the inclusion of altimeter backscatters has a positive impact on the wind quality over the HSCAT nadir region. Finally, the potential approaches to further improve the combined scatterometer and altimeter wind inversion are summarized.

Synthetic aperture radar (SAR) has proven to be an important tool for the retrieval of ocean surface currents. However, existing spaceborne SAR systems can usually measure only one component of an ocean current vector. In this article, we propose a new concept of dual-look spaceborne SAR system for ocean surface motion remote sensing. The key of the proposed SAR system lies in the use of a technique called intrapulse beam switching (IPBS) implemented by a phased array antenna. One example for the application of the proposed IPBS-based SAR system is its combination with the Doppler centroid anomaly (DCA) method. Through the combination, the DCA method, which in its conventional version can measure only the radial component of a current vector, is generalized to measure full ocean current vectors. A system design example and its performance evaluation demonstrate that the accuracies for ocean surface velocity vector measurement better than 5 cm/s in both azimuth and range, and better than 10° in velocity direction for a mild current, and a swath width of about 100 km, can be achieved. A comparison with other beam-generating schemes indicates that a relatively large swath width, without compromising the current-measuring accuracy, can be achieved by the proposed SAR system with one single antenna array and one single physical output channel-a feature that means a high level of integration which in turn allows for the flexibility to operate this system in multiple SAR modes.

This paper proposes a new scheme of motion parameter estimation and relocation for airborne three-channel circular stripmap synthetic aperture radar (CSSAR)-ground moving target indication (GMTI) systems. Compared with the conventional straight-path SAR, the parameter estimation of a target is more challenging because the target's range history and signal model are more complicated due to the complexity of the relative motion between CSSAR and ground moving target. In this paper, the signal model of a ground moving target and the expression for its along-track interferometric (ATI) phase from the environment of airborne three-channel CSSAR are derived. The coupling effect among the target's motion and position parameters is also figured out. Then, a scheme of motion parameter estimation and relocation is proposed. The proposed scheme utilizes the ATI phase and the quadratic-term coefficient in the range equation to estimate the target's motion and position parameters and utilizes an iterative strategy to address the coupling effect among these parameters. Numerical simulations are conducted to validate the satisfactory performance achieved by the proposed algorithm.

We present a new algorithm for suppressing azimuth ambiguities when measuring surface currents with an along-track interferometric (ATI) synthetic aperture radar in heterogeneous scenes, such as coastal waters or rivers. The key of the proposed algorithm involves a careful analysis of a parameter called the eigenvalue spectrum entropy (EVSE), which is defined as the entropy of the eigenvalue spectrum of the ATI covariance matrix computed in the Doppler domain. The physical meaning of EVSE is that it serves as a descriptor for the degree to which an unambiguous signal component and an ambiguous one are mixed. With the help of EVSE, azimuth ambiguities can be suppressed. Simulation results demonstrate that as compared with the conventional ATI method without azimuth ambiguity suppression, the proposed algorithm allows for a pronounced improvement in the current measuring accuracy. Other advantages of the proposed algorithm lie in the fact that it is not only adaptive, due to its ability to automatically capture the useful Doppler band whose width and position may both vary for different radar and scene parameters, but it also needs a minimal number of user inputs, making it a quite attractive algorithm for routine implementation.

This paper deals with the issue of ground moving target imaging and motion parameter estimation with an airborne dual-channel circular stripmap synthetic aperture radar (CSSAR) system. Although several methods of ground moving target motion parameter estimation have been proposed for the conventional airborne linear stripmap SAR, they cannot be applied to airborne CSSAR because the range history of a ground moving target for airborne CSSAR is different than that for airborne linear stripmap SAR. In this paper, the moving target's range history for airborne dual-channel CSSAR and the target signal model after the displaced phase center antenna processing are derived, and a new ground moving target imaging and motion parameter estimation algorithm is developed. In this algorithm, the estimation of baseband Doppler centroid and its compensation are first performed. Then focusing is implemented in the 2-D frequency domain via phase multiplication, and the target is focused in the SAR image without azimuth displacement due to the compensation of the Doppler shift caused by its motion. Finally, the target's motion parameters are estimated with its Doppler parameters and its position in the SAR image. Numerical simulations are conducted to validate the derived range history and the performance of the proposed algorithm.

This paper deals with signal reconstruction for multichannel high-resolution wide-swath synthetic aperture radar (HRWS-SAR) systems. One of the commonly used algorithms for processing HRWS-SAR data is Krieger's digital beamforming (DBF) algorithm. This algorithm works quite well for cases with uniform space-time sampling as well as moderately nonuniform sampling. However, for cases with highly nonuniform sampling, Krieger's DBF algorithm in its original form suffers from a severe degradation in the signal-to-noise ratio, and for cases with coinciding sampling, this algorithm even fails to function. In this paper, we will solve these problems such that an improved DBF (IDBF) algorithm is developed. The key of the IDBF algorithm consists of two procedures: The first one implements an operation called ambiguity-index screening, which is based on two novel quantities, termed the equivalent sampling spacing and the effective reconstructed Doppler bandwidth; and the other key procedure implements a Doppler-spectrum weighting based on a newly defined parameter that is termed the maximum-to-minimum ratio of the noise spectrum. Simulation results show that the newly proposed IDBF algorithm shares a pronounced improvement in the imaging performance over Krieger's DBF algorithm. Moreover, simulation results also demonstrate that the IDBF algorithm exhibits a more robust and consistent overall performance than several other existing reconstruction algorithms.

This paper deals with synthetic aperture radar (SAR) raw data simulation for ocean scenes featuring surface waves and currents, an issue which has proven to be of great necessity in preparing for future oceanic SAR missions. In this paper, the inverse Omega-K (IOK) algorithm, which is originally designed for SAR raw data simulation of stationary land scenes, is extended to ocean scenes. To realize such a generalization, endeavors are made in two aspects. First, specially aimed at ocean dynamics of ocean waves and currents, the 2-D spectrum of the SAR signal is derived. Second, to account for the spatial variation of ocean-motion parameters, we adopt a strategy called batch processing, whose basic feature is that a single implementation of the IOK algorithm will simultaneously simulate a collection of ocean-surface backscattering elements that have the same radial velocity. For the proposed simulator, the velocity bunching effect is embodied via making the long-wave radial orbital velocities physically enter the range equation of the SAR raw signal, instead of superimposing this effect onto the reflectivity map. The spread of the facet velocities within one resolution cell enters the raw data through a random perturbation of the local long-wave orbital velocity. The proposed simulator is not only rather accurate due to the fact that, in deriving the range frequency mapping function, no Taylor expansion is made on the range equation, but also much more efficient than its time-domain counterpart. Effectiveness of the proposed simulator is validated by using simulation results.

In this letter, a novel ground moving target imaging algorithm suitable for high-resolution synthetic aperture radar (SAR) is proposed. The key step of the proposed algorithm is to make a moving target equivalent to a static one based on the derived equivalent range equation. Due to such equivalence, the commonly used standard algorithms for stationary scene imaging (e.g., the range Doppler algorithm) can be easily adapted to focus moving targets by adding only a search operation. The proposed algorithm does not make any approximation to the range equation and is thus rather suitable for high-resolution imaging of moving targets. In addition, due to the used equivalence, to focus a slow-moving target with four unknown parameters (two motion parameters plus two position parameters), the dimensionality of the parameter search space is reduced to one. Experimental results of the simulated data validate the proposed algorithm.

This paper deals with target-detection issues in extremely heterogeneous environments, with a multichannel synthetic-aperture-radar-based ground moving-target indication (SAR-GMTI) system, and proposes a new detector with the aim of addressing such extremely heterogeneous environments. The proposed detector is a multistage one: The first detection stage implements the conventional Displaced Phase Center Array test, but the second stage implements a new test, which is called the Degree of Radial-Velocity Consistency (DRVC) test. We will show that the newly developed DRVC test possesses two pronounced characteristics. The first characteristic is that the DRVC test incorporates such a priori knowledge that the radial velocities corresponding to the individual components of a moving target are all equal, while the second characteristic of the DRVC test is its clutter-heterogeneity-independent property. The two characteristics make the proposed detector a good candidate for addressing extremely heterogeneous environments. Simulation results demonstrate that the proposed detector outperforms several existing detectors, particularly in the capacity to handle extremely heterogeneous environments. Moreover, the application of the proposed detector to a set of real-measured three-channel airborne SAR-GMTI data further demonstrates the efficacy of the proposed detector.

This letter deals with the issue of moving-target relocation in wide-area ground moving-target indication for dual-channel radar systems. Due to channel mismatch, along-track baseline error, the existence of across-track baseline, etc., it is difficult to accurately relocate the detected targets. In this letter, we propose a new knowledge-based (KB) method for target relocation. The key idea of the proposed method is to use such knowledge that a moving target and its neighboring clutter, which is situated at the same azimuth angular position and the same range cell as this target in the observed scene, have the same interferometric phase. This new KB method, as an indirect one, does not employ the conventional relocation formula and therefore is not influenced by most of (if not all) interferometric phase errors. Experimental results from real radar data demonstrate a fairly high degree of target relocation accuracy.

For interferometric synthetic aperture radar (InSAR), the second moment of interferometric phase, i.e., its variance, is a useful metric for InSAR applications (e.g., configuration design). Due to the high degree of nonlinearity in the probability density function of the multilook interferometric phase, it is extremely difficult to derive the analytical expression of the interferometric-phase variance as a function of the number of looks. However, in this letter, we will show that, if we follow an indirect route, then an analytical formula for approximating the interferometric-phase variance for any number of looks can be obtained. The key step of deriving this analytical formula is to transform the interferometric phase into the Euler domain. Simulation results show an excellent agreement between the measured variance curve and the curve obtained by the newly proposed formula except for some small coherence values.

For multichannel synthetic aperture radar based ground moving-target indication (SAR-GMTI), the effective baseline usually needs to be estimated in order to obtain an accurate estimate of radial velocity for each moving target. This paper deals with the effects of Doppler aliasing on baseline estimation. We show that Doppler aliasing can introduce an interferometric phase uncertainty as well as an interferometric phase bias. The phase uncertainty will increase the variance of the baseline estimate, whereas the phase bias will bias the baseline estimate. To address the aforementioned effects caused by Doppler aliasing, a new method for estimating the effective baseline is proposed. One of the key steps of this method is to perform an operation called sample censoring aimed at mitigating the problem of estimation bias. The censoring threshold can be approximately determined by introducing a concept referred to as equivalent variance for the interferometric phases of the entire Doppler bins. Moreover, in order to account for the variation of interferometric phase variance over different Doppler bins, a strategy of weighting is adopted. Experimental results from SAR-GMTI data validate the effectiveness of the newly proposed baseline estimation method.

Based on the method of series reversion, Neo developed a quite accurate range Doppler algorithm (RDA). In performing this RDA, the range derivatives need to be updated along the range. In this letter, first, we will give an analytical method to update the range derivatives for this RDA. The proposed method mainly exploits two points the first is the introduction of a reference vector on the ground plane of the bistatic geometry, and the second is the use of the principle of series reversion. Second, based on this new method of updating the range derivatives, we present a simple image registration method for mapping the focused image onto the ground plane, which needs a 1-D interpolation only in the range direction. Third, a motion compensation method is also proposed.

A novel approach to motion parameter estimation with low pulse repetition frequency (PRF) sampling based on compressed sensing (CS) theory is introduced. As is known to us, when PRF is less than the Doppler spectrum bandwidth, moving targets suffer both Doppler centroid frequency ambiguity and Doppler spectrum ambiguity. Under this condition, the traditional parameter estimation method in the Doppler domain is out of action. The key of this letter converts motion parameter estimation in the synthetic aperture radar system with low PRF sampling into solving an optimization equation based on CS theory. Because moving targets in the scene can be regarded as sparse signals after clutter cancellation, an optimization algorithm based on CS theory is proposed to reconstruct sparse signals and meanwhile estimate the along-track velocities and azimuth positions of moving targets. Considering the fact that range cell migration of moving targets is not subject to PRF limitations, Radon transform is adopted to obtain unambiguous across-track velocities and range positions. Results on simulation and real data are provided to show the effectiveness of this method.

This paper deals with an omega-K algorithm for focusing bistatic synthetic aperture radar (SAR) data. The key of the proposed algorithm is the derivation of a frequency mapping function by using Neo's method of series reversion. The registration of the focused image onto the ground plane is discussed in detail, which is based on a conclusion that the targets whose instantaneous Doppler frequencies at zero azimuth time are the same as that of the reference target at zero azimuth time will all be focused at the reference target's azimuth position in the focused image. The range invariance region size, which the proposed algorithm can process, is also determined in this paper. The proposed algorithm can handle extreme bistatic configurations with wide apertures and large squint angles. The effectiveness of the proposed algorithm is confirmed by simulation results. Although developed for the azimuth-invariant case, the proposed algorithm can be readily extended to the azimuth-variant case, as long as we divide the SAR data into blocks in the azimuth direction so that each block of SAR data can be assumed quasi-stationary in the azimuth direction.

For high-quality synthetic aperture radar (SAR) processing, Doppler centroid ambiguity resolving is an essential procedure. A novel method for the resolution of Doppler ambiguity is presented which exploits the fact that, in the compressed azimuth time and range frequency domain, all targets span the same range frequency bandwidth and exhibit the same slope which is just proportional to the Doppler ambiguity number. The slope is removed by interpolation so that a simplified Radon transform can be applied. The use of entropy to find the maximum concentration of the Radon-transformed image can improve the robustness of the method. The proposed method directly gives a reliable estimate of the Doppler ambiguity number and is not affected by the azimuth partially covered targets. Experimental results show that the proposed method works well in medium- to high-contrast scenes.