Small Grid Research Articles

Decentralized Path Planning for Multi-Objective Robot Swarm System

The multi-robot path planning aims to explore a set of non-colliding paths with the shortest sum of lengths for multiple robots. The most popular approach is to artificially decompose the map into discrete small grids before applying heuristic algorithms. To solve the path planning in continuous environments, we propose a decentralized two-stage algorithm to solve the path-planning problem, where the obstacle and inter-robot collisions are both considered. In the first stage, an obstacle- avoidance path-planning problem is mathematically developed by minimizing the travel length of each robot. Specifically, the obstacle-avoidance trajectories are generated by approximating the obstacles as convex-concave constraints. In the second stage, with the given trajectories, we formulate a quadratic programming (QP) problem for velocity control using the control barrier and Lyapunov function (CBF-CLF). In this way, the multi-robot collision avoidance as well as time efficiency are satisfied by adapting the velocities of robots. In sharp contrast to the conventional heuristic methods, path length, smoothness and safety are fully considered by mathematically formulating the optimization problems in continuous environments. Extensive experiments as well as computer simulations are conducted to validate the effectiveness of the proposed path-planning algorithm.

A Bayesian Network Approach to Evaluating the Effectiveness of Modern Mine Hunting

This paper describes a novel technique for estimating how many mines remain after a full or partial underwater mine hunting operation. The technique applies Bayesian fusion of all evidence from the heterogeneous sensor systems used for detection, classification, and identification of mines. It relies on through-the-sensor (TTS) assessment, by which the sensors’ performances can be measured in situ through processing of their recorded data, yielding the local mine recognition probability, and false alarm rate. The method constructs a risk map of the minefield area composed of small grid cells (~4 m2) that are colour coded according to the remaining mine probability. The new approach can produce this map using the available evidence whenever decision support is needed during the mine hunting operation, e.g., for replanning purposes. What distinguishes the new technique from other recent TTS methods is its use of Bayesian networks that facilitate more complex reasoning within each grid cell. These networks thus allow for the incorporation of two types of evidence not previously considered in evaluation: the explosions that typically result from mine neutralization and verification of mine destruction by visual/sonar inspection. A simulation study illustrates how these additional pieces of evidence lead to the improved estimation of the number of deployed mines (M), compared to results from two recent TTS evaluation approaches that do not use them. Estimation performance was assessed using the mean squared error (MSE) in estimates of M.

Research on Multi-Agent Systems in a Smart Small Grid for Resource Apportionment and Planning

With the advancement in the technology, deployment of sensors in the industrial or public building is increasing rapidly. The basic aim is to obtain the data from the environment and decision making to the energy saving. The activities caused by the human results the undergoing negative change in the environment. There are many techniques available for decision making and consider the environmental factors solely which cause the energy consumption. However, user’s preferences are not adapted by the systems, but at energy consumption optimization, these systems are very successful. The end-users use the system which considers the factors and their wellbeing are get affected. The distributed generation is incorporated by the Smart Small Grid (SSG), communication network and the sensors for the more reliable, flexible and efficient grid. The energy saving system is presented in this paper which also adapts to the inhabitants preferences apart from environmental conditions consideration. The architecture of Multi-Agent System (MAS) and the agents are utilized for negotiation process performance between the users comfort preferences and optimization degree that according to these preferences, achievement of system is done. The energy consumption of 40% is obtained and in the inhabitants' behavior pattern, the algorithm was specialized. The 16.89% of reduction is obtained by the existing system and it was focused to obtain the agreement between the system and users for user preference satisfaction and the energy optimization is also performed at the same time.

A comprehensive approachfor off-road trafficability evaluation and development of modified equation for estimation of RCI to assessregional soil variation using geospatial technology

The information of terrain is highly valuable as the accuracy of decision maker depends on input data for taking the correct decision. For planning of any successful off-road movement, the terrain information plays the vital role. This paper describes the state of art of off-road trafficability leading from the contributing factors, Instruments for measurements and trafficability mapping techniques in chronological order. In modern times, the number & type of tracked or wheeled vehicles, has increased many times, therefore off-road trafficability for operation planning became a complex task to handle. The accuracy and reliability of measurements involved in trafficability will play a major role for any successful operation. Off-road trafficability shows the capacity of soil required for vehicular movement. Remolding Cone Index (RCI) indicates the soil's capability for off-road movement. In this study, the area was divided in equal small grids for ease of computation of RCI. Geospatial technology provides the platform to determine the locations of observation points as well as the extrapolation of information of inaccessible area using geospatial tools and techniques. RCI values were computed for each grid and also measured with cone penetrometer in the field. R2 value for observation values was determined for different soils present in the area to check the accuracy of measurements and then based on observed value and computed value, R squared (coefficient of determination) values (0.7754 and 0.4867) were evaluated for both study areas to get the idea about relevance, reliability and accuracy. Residual RCI (RRCI), difference of computed & observed was also analyzed for different soils for different moisture conditions. Based on thisanalysis, a modified equation was developed for different type of soils present in the study area. This development will pave the way to compute the RCI accurately, which will be used to assess the off-road trafficability of other areas in similar manner. Therefore, this study is useful to assess the regional variation of soil behavior towards trafficability based on modified equation.

Численное моделирование пожара в автодорожном тоннеле. Выбор расчетной сетки

Рассматривается вопрос выбора расчетной сетки при моделировании пожара в тоннеле с помощью полевого метода и проводится оценка возможного влияния размеров ячеек сетки, а также граничного условия постоянства давления на результаты расчета. Выполнено моделирование пожара для четырех размеров расчетной сетки. Обоснована возможность применения наиболее грубой из используемых сеток с точки зрения инженерных расчетов, в том числе с оговоркой относительно постановки граничного условия. The issue of fire safety of road tunnels is currently an urgent task. Road tunnels are usually not standard typical facilities, but the unique structures. Therefore, it is necessary to study the influence of various parameters on the development of fire in order to take into account the characteristics of a particular object and make decisions on its effective fire protection. Implementation of field tests in this case is expensive and time-consuming. In this regard, numerical modeling is one of the most effective methods of such research. Field models are the most common and currently used for numerical calculations. These models are based on the numerical solution of the system of conservation equations for small control volumes of the calculation grid. This paper examines the issues of selection the calculation grid when modeling a fire in tunnels using the field method is considered and the possible influence of the size of the grid cells is estimated. The mathematical model used in this work is based on a set of differential equations of hydrodynamics, heat transfer, as well as the equation of conservation of the masses of components. Four computational grids were selected for a horizontal (without slope) model tunnel to determine the optimal cell size. As a result of conducted calculations it was established the following: the size of calculated grid is not fundamental for the initial stage of the fire; the use of smaller grid may be preferable at further development of fire, accompanied by increase of combustion capacity to the maximum; the maximum temperature values, especially in the far sections, are obtained on the coarsest grid. The use of such a grid for estimated engineering calculations can be allowed.

High‐resolution passive imaging by electromagnetic vortex beams

AbstractA new scheme to achieve high resolution in passive millimeter wave imaging (PMMWI) using electromagnetic (EM) vortex beams is proposed in this article. The spatial resolution of the traditional PMMWI system based on the mechanically or electronically controlled scanning scheme is mainly limited by the beam width of the receiver. However, it is not practical to fabricate an antenna that is too large, another possible way to improve the resolution is to increase the sampling points but will increase the imaging time. In this article, the multimode EM vortex beam is applied to achieve high resolution with less sampling points. The imaging scene is first discretized into small grid cells, and then multimode measurements are conducted during the scanning process to construct equations to solve the unknown brightness distribution. The compress sensing method is applied to reduce the number of orbital angular momentum mode. Simulation results demonstrate that high resolution can be achieved by the proposed method.

Investigating the impact of spatial-temporal grid size on the microscopic forecasting of the inflow and outflow gap in a free-floating bike-sharing system

Free-floating bike-sharing systems have rapidly gained popularity as a viable short-distance transportation mode. As users play a significant role in the movement of the bikes in such a system, the basis for evaluating bike usage is to predict the gap between the locking and unlocking behaviour in a specified grid, which is defined as the inflow and outflow gap. The Spatial-Temporal grid size, including its time and space dimensions, has a significant impact on the microscopic forecasting of the inflow and outflow gap. In this study, a flexible framework for testing the impact of the grid on inflow and outflow gap predictions is proposed. The performance of four algorithms, i.e., linear regression, support vector regression, random forest, and gradient boost machine, was compared for different grid sizes based on the dataset provided by the Shanghai Big Data Joint Innovation Laboratory. The results show that the proposed framework can be used to evaluate the impact of grid size on microscopic forecasts. A smaller grid helps to achieve better model prediction results, but it also involves longer calculation time. Comparisons of the four algorithms show that the larger the spatial dimensions of the grid, the worse the predicted results. Excluding random forest, the other algorithms tend to achieve better results when the temporal dimension of the grid is larger. The gradient boost machine algorithm provides the best results in most scenarios; the optimal spatial-temporal grid side length is 200 m, 24 h with 5 by 5 grid combination. Dispatchers or analysts in bike-sharing companies can refer to the proposed framework to select the bike delivery scale and management scope. In addition, this study will help researchers and practitioners quickly select the appropriate grid size and machine learning algorithms for bike-sharing analysis.

Quantification of the Nano-Voids in Electroless Deposited Copper Layers Using SiNx TEM Grids

A plan-view analytical method to detect nano-voids of deposited copper layers, especially for the fabrication of printed circuit boards, was investigated using transmission electron microscopy (TEM). Through electroless plating, thin copper layers were directly deposited on small silicon nitride window grids, and the presence of nano-voids within the deposited copper layers were confirmed with various TEM analytical techniques. The amount and size of the nano-voids were further quantified from the plan-view TEM images, making it possible to compare quickly multiple samples prepared under various plating conditions. This analytical method is practical as it is faster in detecting and measuring nano-scale defects when compared to typical cross-sectional analytical methods.

A Cover-Based Approach to Multi-Agent Moving Target Pursuit

We explore the task of designing an efficient multi-agent system that is capable of capturing a single moving target, assuming that every agent knows the location of all agents on a fixed known graph. Many existing approaches are suboptimal as they do not coordinate multiple pursuers and are slow as they re-plan each time the target moves, which makes them fare poorly in real-time pursuit scenarios such as video games. We address these shortcomings by developing the concept of cover set, which leads to a measure that takes advantage of information about the position and speed of each agent. We first define cover set and then present an algorithm that uses cover to coordinate multiple pursuers. We compare the effectiveness of this algorithm against several classic and state-of-the-art pursuit algorithms, along several performance measures. We also compute the optimal pursuit policy for several small grids, and use the associated optimal scores as yardsticks for our analysis.

Optimal Voltage Compensation of Small Hydropower Grid Linked Structure Centered on PV-STATCOM Smart Inverter

Alternative renewable energy structures for example hydro turbine generators can be utilised to replace or rise in the efficiency of energy distribution infrastructure in remote communities. A small hydro turbine linked to grid divides the load into current and electricity. The voltage amplitude in the energy distribution structure will be changed as a result of the power quality problem, and this will have a direct influence on the electric load. This study introduces the PV-STATCOM, a novel smart inverter that can be used to control a solar inverter as dynamic reactive power compensator (DRPC). The recommended photovoltaic STATCOM can be utilised to offer voltage regulate for serious structure demands. For the night, the whole inverter capacity is utilised for STATCOM operations. The smart inverter temporarily disables its real power generating function during a large system outage throughout the day and makes its whole inverter capacity accessible for STATCOM operation. This research examines the stability of the voltage control structure`s excitation in the Micro Hydro Power Plant. The MOPSO algorithm may be used to regulate the Permanent Magnet Synchronous Machine and control the voltage on the direct current linked part of system. The system will most probably be unstable if the exact definition of system parameters is uncertain. To present the parameter specifications for the stable structure, the DC-link control system is modelled, theoretically assessed, and simulated. This paper proposes the use of a particle swarm optimization centred SVC controller for reactive power optimization and adjustment in a separated hybrid system with micro hydro and wind diesel. The small linear signal model of the hybrid micro hydro Diesel wind model is investigated under various loading scenarios. The SVC controller is compared to the GA-based controller and optimised using the PSO approach. The purpose of study is to employ STATCOM for reactive power compensation in order to increase energy structure's dependable operating limit. It also tries to reduce voltage variations caused by renewable energy sources' variable nature. To obtain an acceptable outcome, the proper modification of Proportional–Integral parameters in STATCOM is conducted consequentially centred on BFA and GA. The STATCOM control circuit's PI controller's settings have been optimised. This article discusses the optimization and adjustment strategies for PID controllers in a STATCOM based circuit for PV-Micro hydro hybrid system voltage stability.

Million node fracture: size matters?

Transmissivity of self-affine fractures was computed numerically as a function of the grid size. One-million-node fractures (1024 × 1024 nodes) with fractal dimensions of 2.2–2.6 were cut into successively smaller fractures (“generations”), and transmissivities computed. The number of fractures in each generation was increased by a factor of 4. Considerable scatter in transmissivity was observed for smaller grid sizes. Average transmissivity of the fractures in the generation decreased with the grid size, without approaching any asymptotic value, which indicates no representative elementary volume (REV). This happened despite the average mean aperture being the same in each generation. The results indicate that it is not possible to estimate the transmissivity of a large fracture by cutting it into smaller fractures, running flow simulations on those and averaging the results. The decrease in transmissivity with the grid size was found to be due to an increase in the flow tortuosity.

CORL 2: Exploring Cooperative Opportunities, Reducing Latency and Prolonging Network Lifetime for Data Collection Using Mobile Sinks in Wireless Sensor Networks

Data collection is one of the most important issues in Wireless Sensor Networks (WSNs). Many data collection algorithms have been proposed for collecting data using multiple mobile sinks. However, the anchor selection strategy, which significantly impacts the network lifetime, still can be improved. In addition, the collaboration between multiple mobile sinks is still rare, resulting in the long latency of each round of data collection. This paper proposes an Exploring Cooperative Opportunities, Reducing Latency and Prolong Network Lifetime algorithm for Data Collection, called CORL <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> , aiming to improve the network lifetime and reduce the latency of data collection. Initially, the proposed CORL <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> partitions the monitoring region into several equal-sized subregions and assigns each mobile sink to each subregion. Then CORL <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> further partitions each subregion into several equal-sized grids and constructs a path passing through all grids in that subregion. To reduce the energy consumption for packet forwarding, the proposed CORL <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> further partitions each grid into several small grids and adjusts the path such that it can pass through high-density small grids, aiming to maximize the number of anchors and prolong the network lifetime. Then the cooperative strategy is applied to cooperatively reduce the maximal latency of data collection in all subregions and balance the data collection workload between neighboring mobile sinks. Performance evaluations reveal that the proposed CORL <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> outperforms existing data collection algorithms in terms of latency, energy consumptions, the workload balancing improving index(WBII), and network lifetime for data collection in the given WSNs.

The Impact of Electric Vehicle Density on Local Grid Costs: Empirical Evidence from Norway

While a rapid shift towards electric vehicles (EVs) will contribute to reducing carbon emissions from the transport sector, there are concerns that uncoordinated charging of EVs might impose challenges for the local electricity grid. Our study is the first to investigate this empirically in a country-wide analysis, using data from the country with the highest market share of EVs, namely Norway. We present the regulatory framework in which Norwegian grid companies operate and discuss the possible impact of EV charging. Using panel data on 107 grid companies over the period 2008-2017, we then estimate the effect of local growth in EVs on local grid costs. We find that increases in EV stock are associated with increases in costs which are both statistically and economically significant. However, there is a lot of heterogeneity in these results, where the effect on grid costs are higher for small grid companies in rural areas.

SPH modelling of companion-perturbed AGB outflows including a new morphology classification scheme

Context.Asymptotic giant branch (AGB) stars are known to lose a significant amount of mass by a stellar wind, which controls the remainder of their stellar lifetime. High angular-resolution observations show that the winds of these cool stars typically exhibit mid- to small-scale density perturbations such as spirals and arcs, believed to be caused by the gravitational interaction with a (sub-)stellar companion.Aims.We aim to explore the effects of the wind-companion interaction on the 3D density and velocity distribution of the wind, as a function of three key parameters: wind velocity, binary separation and companion mass. For the first time, we compare the impact on the outflow of a planetary companion to that of a stellar companion. We intend to devise a morphology classification scheme based on a singular parameter.Methods.We ran a small grid of high-resolution polytropic models with the smoothed particle hydrodynamics (SPH) numerical code PHANTOMto examine the 3D density structure of the AGB outflow in the orbital and meridional plane and around the poles. By constructing a basic toy model of the gravitational acceleration due to the companion, we analysed the terminal velocity reached by the outflow in the simulations.Results.We find that models with a stellar companion, large binary separation and high wind speed obtain a wind morphology in the orbital plane consisting of a single spiral structure, of which the two edges diverge due to a velocity dispersion caused by the gravitational slingshot mechanism. In the meridional plane the spiral manifests itself as concentric arcs, reaching all latitudes. When lowering the wind velocity and/or the binary separation, the morphology becomes more complex: in the orbital plane a double spiral arises, which is irregular for the closest systems, and the wind material gets focussed towards the orbital plane, with the formation of an equatorial density enhancement (EDE) as a consequence. Lowering the companion mass from a stellar to a planetary mass, reduces the formation of density perturbations significantly.Conclusions.With this grid of models we cover the prominent morphology changes in a companion-perturbed AGB outflow: slow winds with a close, massive binary companion show a more complex morphology. Additionally, we prove that massive planets are able to significantly impact the density structure of an AGB wind. We find that the interaction with a companion affects the terminal velocity of the wind, which can be explained by the gravitational slingshot mechanism. We distinguish between two types of wind focussing to the orbital plane resulting from distinct mechanisms: global flattening of the outflow as a result of the AGB star’s orbital motion and the formation of an EDE as a consequence of the companion’s gravitational pull. We investigate different morphology classification schemes and uncover that the ratio of the gravitational potential energy density of the companion to the kinetic energy density of the AGB outflow yields a robust classification parameter for the models presented in this paper.

Joint primary frequency regulation strategy for asynchronous power grids connected by a VSC‐MTDC system

Asynchronous interconnection will reduce the inertia of each grid, and it is difficult for a small inertia grid to maintain frequency stability under the fluctuation of new energy or load. In order to improve the frequency stability of asynchronous power grids connected by a voltage source converters based multi-terminal direct current (VSC-MTDC) system, a joint primary frequency regulation (JPFR) strategy is proposed in this paper. The main principle of the proposed JPFR strategy is firstly to formulate frequency regulation protocols (FRPs) between asynchronous power grids. Next, an improved analytical steady-state model of the VSC-MTDC system is adopted. The improved model can calculate the power reference of each VSC according to the FRP, avoiding the impact on the grid not participating in the protocol. Then, based on the sequential search method, the results of the improved model are modified to prevent overload. Finally, simulations of a four-terminal VSC-MTDC system are carried out for validating the proposed JPFR strategy.

Simulation of the Part Load Behavior of Combined Heat Pump-Organic Rankine Cycle Systems

Pumped Thermal Energy Storages (PTES) are suitable for bridging temporary energy shortages, which may occur due to the utilization of renewable energy sources. A combined heat pump (HP)-Organic Rankine Cycle (ORC) system with suitable thermal storage offers a favorable way to store energy for small to medium sized applications. To address the aspect of flexibility, the part load behavior of a combined HP-ORC system, both having R1233zd(E) (Trans-1-chloro-3,3,3-trifluoropropene) as working fluid and being connected through a water filled sensible thermal energy storage, is investigated using a MATLAB code with integration of the fluid database REFPROP. The influence on the isentropic efficiency of the working machines and therefore the power to power efficiency (P2P) of the complete system is shown by variation of the mass flow and a temperature drop in the thermal storage. Further machine-specific parameters such as volumetric efficiency and internal leakage efficiency are also considered. The results show the performance characteristics of the PTES as a function of the load. While the drop in storage temperature has only slight effects on the P2P efficiency, the reduction in mass flow contributes to the biggest decrease in the efficiency. Furthermore, a simulation for dynamic load analysis of a small energy grid in a settlement is conducted to show the course of energy demand, supplied energy by photovoltaic (PV) systems, as well as the PTES performance indicators throughout an entire year. It is shown that the use of PTES is particularly useful in the period between winter and summer time, when demand and supplied photovoltaic energy are approximately equal.

Unbalanced Current Reduction Method of Microgrid Based on Power Conversion System Operation

In isolated areas such as islands with small power grids, the BESS (Battery energy storage system) can supply the standard voltage and frequency to the power system to achieve 100% of renewable sharing. In addition, the installation of additional BESS may be required in the microgrid due to technical limitations such as redundant operation and manufacturer specifications. Thus, the BESSs in a microgrid can be split into main and sub BESSs which play a role as the main source and auxiliary services, respectively. Generally, the ratio of unbalance current in microgrid system tends to be high, because of inherently unbalanced single phase load distribution. However, because the capacity of BESS is calculated under balanced conditions, the PCS (Power conversion system) of BESS may stop protecting its switching device from a single phase overcurrent in actual operation. From this perspective, this paper proposes that the sub BESSs perform dual current control to supply the unbalanced current instead of the main BESS. In the simulation result of the proposed method, the current unbalance rate of the main ESS has been reduced by about 26%. Through the proposed control scheme, it is possible to prevent an unexpected single phase overload of the main BESS in the microgrid.

Sparse data-driven wavefront prediction for large-scale adaptive optics.

This paper presents a computationally efficient wavefront aberration prediction framework for data-driven control in large-scale adaptive optics systems. Our novel prediction algorithm splits prediction into two stages: a high-resolution and a low-resolution stage. For the former, we exploit sparsity structures in the system matrices in a data-driven Kalman filtering algorithm and constrain the identified gain to be likewise sparse; for the latter, we identify a dense Kalman gain and perform corrections to the suboptimal predictions of the former on a smaller grid. This novel prediction framework is able to retain the robustness to measurement noise of the standard Kalman filter in a much more computationally efficient manner, in both its offline and online aspects, while minimally sacrificing performance; its data-driven nature further compensates for modeling errors. As an intermediate result, we present a sparsity-exploiting data-driven Kalman filtering algorithm able to quickly estimate an approximate Kalman gain without solving the Riccati equation.

CMPC: An Innovative Lidar-Based Method to Estimate Tree Canopy Meshing-Profile Volumes for Orchard Target-Oriented Spray.

Canopy characterization detection is essential for target-oriented spray, which minimizes pesticide residues in fruits, pesticide wastage, and pollution. In this study, a novel canopy meshing-profile characterization (CMPC) method based on light detection and ranging (LiDAR)point-cloud data was designed for high-precision canopy volume calculations. First, the accuracy and viability of this method were tested using a simulated canopy. The results show that the CMPC method can accurately characterize the 3D profiles of the simulated canopy. These simulated canopy profiles were similar to those obtained from manual measurements, and the measured canopy volume achieved an accuracy of 93.3%. Second, the feasibility of the method was verified by a field experiment where the canopy 3D stereogram and cross-sectional profiles were obtained via CMPC. The results show that the 3D stereogram exhibited a high degree of similarity with the tree canopy, although there were some differences at the edges, where the canopy was sparse. The CMPC-derived cross-sectional profiles matched the manually measured results well. The CMPC method achieved an accuracy of 96.3% when the tree canopy was detected by LiDAR at a moving speed of 1.2 m/s. The accuracy of the LiDAR system was virtually unchanged when the moving speeds was reduced to 1 m/s. No detection lag was observed when comparing the start and end positions of the cross-section. Different CMPC grid sizes were also evaluated. Small grid sizes (0.01 m × 0.01 m and 0.025 m × 0.025 m) were suitable for characterizing the finer details of a canopy, whereas grid sizes of 0.1 m × 0.1 m or larger can be used for characterizing its overall profile and volume. The results of this study can be used as a technical reference for the development of a LiDAR-based target-oriented spray system.

Gridless super-resolution sparse recovery for non-sidelooking STAP using reweighted atomic norm minimization

The sparse recovery space–time adaptive processing (SR-STAP) can reduce the requirements of clutter samples and suppress clutter effectively using limited training samples for airborne radar. Commonly, the whole angle-Doppler plane is uniformly discretized into small grid points in SR-STAP methods. However, the clutter patches deviate from the pre-discretized grid points in a non-sidelooking SR-STAP radar. The off-grid effect degrades the SR-STAP performance significantly. In this paper, a gridless SR-STAP method based on reweighted atomic norm minimization is proposed, in which the clutter spectrum is precisely estimated in the continuous angle-Doppler domain without resolution limit. Numerical simulations are conducted and the results show that the proposed method can achieve better performance than the SR-STAP methods with discretized dictionaries and the SR-STAP methods utilizing atomic norm minimization.