Radar Research Articles

Quantum Radar: Theory, Limits, and Practical Applications

This paper provides a detailed exploration of quantum radar technology, focusing on the generation, measurement, and theoretical analysis of quantum-correlated signals in both optical and microwave domains. We examine the mechanisms behind producing entangled signals and their application to improve radar sensitivity and accuracy in noisy environments. A review of key studies is presented, with emphasis on their experimental setups and the limitations that define the potential of quantum radar. By aggregating data on object detection range and analyzing global research trends through visualizations, including a bar chart and a world map, we illustrate the growing interest and research efforts in this domain. Our findings highlight the significant advancements and remaining challenges in developing practical quantum radar systems, as well as the worldwide collaboration driving progress in this cutting-edge field.

СОВРЕМЕННЫЕ СРЕДСТВА И МЕТОДЫ МОНИТОРИНГА ПЛАВАЮЩЕГО МОРСКОГО МАКРОМУСОРА И ВНЕДРЕНИЕ ТЕХНОЛОГИЙ МАШИННОГО ОБУЧЕНИЯ

Marine litter pollution is currently recognized as global problem at the level of all international organizations and conventions related to the marine protection. This review examines modern methods and approaches for detecting floating marine macrolitter. The task of detecting marine litter on the water surface is complicated by a large variety of objects, various degrees of their degradation, predominantly small size, partial immersion in the subsurface layer, colorlessness, disguising within the water, difficult observation conditions. The main approaches today include visual observations (from ships, aircraft), trawling, and remote sensing, especially using radar systems. In the last decade, deep learning methods have made significant progress, which has allowed error recognition and identification to be brought to a new level due to various modifications of artificial neural networks. In this review, we analyze the main research on the presented topic and significant achievements and prospects for the application of artificial intelligence to improve methods for detecting and classifying marine litter larger than 2.5 cm.

ОБЛАСТЬ ПРИМЕНИМОСТИ ДАННЫХ СПУТНИКОВОЙ АЛЬТИМЕТРИИ ДЛЯ ВАЛИДАЦИИ АЛГОРИТМОВ ОЦЕНКИ ВЫСОТЫ ВЕТРОВОГО ВОЛНЕНИЯ

Satellite altimetry stands as one of the paramount sources of information regarding significant wave height, primarily due to its global coverage and near real-time availability. This study evaluates the radius of the quasihomogenity region of the eind waves field is estimated based on in situ and altimetry measurements. In situ data were collected during five marine expeditions utilizing drifting wave buoys (Spotter) and the Sea Vision radar system. Ten altimetric missions (Level 3) provided by CMEMS, as well as ERA5 reanalysis of wind speed, were processed. The outcome of the study is an assessment of the maximum radius circle centered on the satellite measurement point, within which the wave field can be considered homogeneous, enabling the use of altimetry data as reference for comparison with other data sources, as well as a methodology for refining this estimate taking into account the heterogeneity of the wind field.

A high-gain gap waveguide-based 16 × 16 slot antenna array with low sidelobe level for mmwave applications

This study presents the design of a high-gain 16 × 16-slot antenna array with a low sidelobe level (SLL) using a tapered ridge gap waveguide feeding network for Ka-band applications. The proposed antenna element includes four cavity-backed slot antennas. A tapered feeding network is designed and utilized for unequal feeding of the radiating elements. Ridge gap waveguide technology is used to reduce the feeding network loss and achieve a low-loss array antenna. The feed layer of the proposed antenna is coupled to a standard rectangular waveguide (WR-28) using a proper transition. The measured results show an impedance bandwidth of more than 17% over the frequency range of 27.5–32.6 GHz covering one of the standard vehicle-to-satellite band (29.4–31.0 GHz) and 5G mmWave N261 band (27.5–28.35 GHz), a maximum gain of 28.9 dBi, and SLL lower than − 20 dB. Thanks to its high performance and desirable features, the proposed antenna shows potential for use in vehicular radar systems and high data rate mmWave communications.

МАТЕМАТИЧНА МОДЕЛЬ СИГНАЛУ ІЗ ЗАДАНИМИ ПОЛЯРИЗАЦІЙНИМИ ПАРАМЕТРАМИ В ОРТОГОНАЛЬНОМУ ПОЛЯРИЗАЦІЙНОМУ БАЗИСІ

The experience of combat operations in the context of the large-scale invasion of Ukraine by the russian federation shows that the current level of development of electronic weapons is characterised by a wide variety of types and types of electronic means, the use of multifunctional means with widely variable signal parameters and operating modes. For example, modern (state-of-the-art) ground, air and sea radar stations use deliberate changes in the frequency, time and polarisation parameters of emitted signals in different modes of operation, depending on the tasks and conditions of a complex electronic environment. The presence of differences in the polarisation parameters of signals objectively creates prerequisites for their consideration in processing in order to improve the detection, recognition and direction finding performance of radio monitoring systems in a complex electronic environment. The approach is based on the use of antennas with orthogonal polarisation antenna elements, which allows signals to be represented as polarisation vectors. During the processing, it is necessary to take into account the influence of the polarisation characteristics of the antenna system on the parameters of the polarisation vector (change of the polarisation basis), which is relevant since the signals are received by the antenna system from different angular directions. An important condition for obtaining objective results when studying the efficiency of polarisation processing algorithms is the use of a correct mathematical model of signals with given polarisation parameters in a certain orthogonal polarisation basis, as well as the use of signals from real radio equipment whose polarisation parameters can be determined in a polarisation basis other than the specified one. The article presents a mathematical model that allows expressing the field components through the parameters of the polarisation ellipse, and also gives expressions describing the relationship between polarisation vectors and their covariance matrices in different polarisation bases of the antenna system.

OPTIMIZATION OF RADIO SYSTEM STRUCTURES FOR DIRECTION FINDING OF SIGNAL SOURCES WITH COMPLETELY KNOWN PARAMETERS

Context. Direction finders are critical components of radar and radio navigation systems, particularly when installed onboard UAVs. The increasing use of unmanned systems has heightened the need for precise direction finding and wide-angle unambiguous measurements. The primary challenge is to strike a balance between achieving high accuracy and maintaining a broad range of unambiguous measurement angles. Objective. To simultaneously enhance direction finding accuracy and expand the range of unambiguous measurement angles through the statistical synthesis of functionally deterministic signal processing methods in multichannel direction finders. Method. The approach is grounded in the statistical theory of optimization for radio remote sensing and radar systems. For the specific type of signals considered in this study, represented by functional-deterministic models, the likelihood function is constructed, and its maxima are determined for various configurations of multi-antenna direction finders. The statistical synthesis results are validated through simulation and in-situ experiments. Results. Theoretical analysis and simulation modeling confirm that in dual-antenna direction finders, there is a trade-off between high resolution and the range of unambiguous direction finding angles. An improved signal processing method is developed for a four-antenna direction finder, utilizing a pair of high-gain and a pair of low-gain antennas. To achieve the maximum possible bearing accuracy within the range of unambiguous direction finder measurements, a new signal processing method is synthesized for a sixelement radio receiver, combining the processing of signals in two amplitude direction finders and one phase direction finder. Conclusions. The proposed approach achieves an optimal balance between resolution and angle range, making it particularly suitable for onboard systems of unmanned aerial vehicles. Simulation results confirm the effectiveness of the proposed method, highlighting its potential for implementation in modern radio systems.

Статистики вищих порядків в задачах виявлення сигналів на фоні корельованих негаусових завад

Signal detection in noise is critical in telecommunications, navigation and radar systems, image processing and biomedical research, where noise often deviates from a normal distribution, and sample values exhibit statistical dependence. Traditional methods for analyzing and designing such systems face significant limitations, including algorithmic and computational complexity, severely restricting their practical application. An effective approach to developing signal detection systems involves using moment and cumulant descriptions of random variables, simplifying the design of detection systems for signals with various probability density functions. The authors propose a novel approach based on one-dimensional (1D) and two-dimensional (2D) moment-cumulant models to describe correlated non-Gaussian processes. This approach enables the modification of the moment-based criterion for statistical hypothesis testing and synthesising polynomial stochastic decision rules for detecting signals in correlated non-Gaussian noise. The study demonstrates that the nonlinear processing of sample values and the application of higher-order statistics to describe the investigated processes account for the structure of non-Gaussian noise and its statistical dependencies. This reduces the error probabilities of the synthesized decision rules compared to traditional Gaussian models. The study aims to enhance the efficiency of signal detection systems under additive interaction with correlated non-Gaussian noise by developing new moment-cumulant models of the investigated processes, modifying the moment-based criterion for hypothesis testing, and designing polynomial decision rules. The study's practical significance lies in creating simple-to-implement algorithms with high accuracy that achieve lower error probabilities in decision rules compared to existing methods.

Real-Time Interference Mitigation for Reliable Target Detection with FMCW Radar in Interference Environments

Frequency-modulated continuous-wave (FMCW) millimeter-wave (mmWave) radar systems are increasingly utilized in environmental sensing due to their high range resolution and robust sensing ability in severe weather environments. However, mutual interference among radar systems significantly degrades the target detection capability. Recent advancements in interference mitigation utilizing deep learning (DL) approaches have demonstrated promising results. DL-based approaches typically have high computational costs, which makes them unsuitable for real-time applications with strict latency requirements and limited computing resources. In this paper, we propose an efficient solution for real-time radar interference mitigation. A lightweight transformer, which is smaller and faster than the baseline transformer, is designed to reduce interference. The integration of linear attention mechanisms with depthwise separable convolutions significantly reduces the network’s computational complexity while maintaining a comparable performance. In addition, a two-stage knowledge distillation (KD) process is deployed to compress the network and enhance its efficiency. The staged distillation approach alleviates the training difficulties associated with substantial differences between the teacher and student networks. Both simulated and real-world experiments demonstrate that the proposed method outperforms the state-of-the-art methods while achieving high processing speeds.

Method for Increasing the Linearity of The Phase in The Approximation Phase On 5G Antennas Using Modified Functions of The Subtractors

The possibility of reducing the phase distortion of the signal spectra in the input paths at the stage of approximation of frequency characteristics is shown. Noticeable progress in the technology of satellite and mobile telecommunications systems, as well as in radar systems, is largely associated with the use of broadband and ultra-broadband signals. Thus, in 2012-2013, the development of Wideband High Frequency (WBHF) radio technology (hereinafter referred to as broadband HF (HF) radio communication) took place in the direction of increasing data transmission rates over HF (HF) radio channels to meet the needs of subscribers of the armed forces of NATO countries. The development of broadband HF (HF) radio communication has led to the revision of the following NATO standards and their release in a new edition: - MIL-STD-188-110C «Interoperability and operational requirements for data modems», 03.01.2012; - MIL-STD-188-141C «Functional compatibility and operational requirements for medium and high frequency radio frequency systems», 12/27/2011. The work carried out experiments to compare frequency characteristics. The changes are also related to the introduction of broadband HF (HF) radio communication technology, which defines a family of broadband modulation types for a radio channel with the necessary bandwidth of the end-to-end amplitude-frequency response (AFC) of the transceiver path from 3 kHz to 24 kHz in 3 kHz increments.

Two pilot case studies for bridge-scour monitoring

Bridge scour is a leading cause of bridge failures worldwide, exacerbated by climate change and increasing flood risks. Real-time data collection plays a critical role in effective flood risk management and decision-making, ultimately enhancing infrastructure resilience. The EU-funded RAMOBRIS (Risk Assessment and Monitoring for Bridges under Scour Hazard) project investigated cost-effective monitoring approaches to develop a novel, multidisciplinary strategy for assessing the risk of critical bridges exposed to scour. This manuscript outlines the monitoring strategy developed during the project, with a focus on the application of cost-effective sensors for hydraulic monitoring. The adopted methodology employs an indirect approach using low-cost remote sensing sensors to assess hydraulic properties and estimate scour depth through advanced formulas. Two pilot case studies were conducted on high-risk masonry bridges over the River Nith in Scotland. Various sensors were installed to evaluate their effectiveness in capturing hydraulic data and monitoring scour dynamics. Data from low-cost sensors were evaluated against data collected from higher-cost sensors or other available datasets. The results showed that low-cost sensors for measuring water levels provided accuracy comparable to high-cost radar systems, while being more cost-effective and easier to install. Video data from solar cameras enabled extensive measurements of surface velocity and discharge, improving the understanding of flow dynamics. The study confirmed the feasibility of using image velocimetry techniques for long-term estimation of river velocity and discharge, although further validation is required. These findings highlight the potential of low-cost and innovative sensor technologies. The open-access dataset generated in this study, which will be periodically updated with new data, provides a valuable resource of real-world information for ongoing research in hydraulic monitoring and bridge safety assessment.

Long Coherent Processing Intervals for ISAR Imaging: Combined Complex Signal Kurtosis and Data Resampling

Airborne inverse synthetic aperture radar (ISAR) imaging of maneuvering targets is important for maritime surveillance. Long coherent processing intervals (CPIs) can bring better resolution and signal-to-clutter-plus-noise ratio (SCNR). Due to the change in the effective rotation vector (ERV), the conventional Range-Doppler (RD) algorithm is not appropriate for producing a well-focused image. To resolve the above issue, we propose a long CPI imaging algorithm through ERV estimation and data resampling. This algorithm estimates the Doppler length of the sub-aperture image by complex signal kurtosis (CSK) at first. Then, the change in the ERV can be estimated because the ship Doppler length is always proportional to the ERV. Finally, the echo is resampled according to the estimation of the time-varying ERV to obtain the echo from a constant ERV. Computer simulation experiments and measured data have verified the effectiveness of the proposed method. Experimental results demonstrate that the proposed method can achieve ISAR imaging with longer CPIs at low SNR and inhomogeneous clutter.

Efficient hardware implementation of ROM-free LFM waveform generation for real-time reconfigurable software-defined radar

Abstract This paper presents a novel method for generating Linear Frequency Modulation (LFM) waveforms. Conventional Look-Up Table (LUT)-based method require large storage resources, especially in high-resolution, multi-mode radar systems. To address this issue, we propose a ROM-free, real-time LFM waveform generator. It uses the fourth-order Runge-Kutta (RK-4) method to solve differential equations for the in-phase and quadrature components. The proposed approach dynamically generates LFM waveforms using only parameters such as pulse width, bandwidth, and sampling rate, eliminating the need for pre-calculated waveforms and LUTs. This method completely removes storage requirements, enabling faster synthesis times and achieving minimal latency. The generator’s performance is validated through simulation and FPGA implementation using a full hardware description language. Results confirm its effectiveness, making it a strong candidate for advanced radar systems that demand high performance with limited hardware resources.

Ice thickness and bed topography of Jostedalsbreen ice cap, Norway

Abstract. We present an extensive dataset of ice thickness measurements from Jostedalsbreen ice cap, mainland Europe's largest glacier. The dataset consists of more than 351 000 point values of ice thickness distributed along ∼ 1100 km profile segments that cover most of the ice cap. Ice thickness was measured during field campaigns in 2018, 2021, 2022 and 2023 using various ground-penetrating radar (GPR) systems with frequencies ranging between 2.5 and 500 MHz. A large majority of the ice thickness observations were collected in spring using either snowmobiles (90 %) or a helicopter-based radar system (8 %), while summer measurements were carried out on foot (2 %). To ensure accessibility and ease of use, metadata were attributed following the GlaThiDa dataset (GlaThiDa Consortium, 2020) and follow the FAIR (findable, accessible, interoperable and reusable) guiding principles. Our findings show that glacier ice of more than 400 m thickness is found in the upper regions of large outlet glaciers, with a maximum ice thickness of ∼ 630 m in the accumulation area of Tunsbergdalsbreen. Thin ice of less than 50 m covers narrow regions joining the central part of Jostedalsbreen with its northern and southern parts, making the ice cap vulnerable to break-up with future climate warming. Using the point values of ice thickness as input to an ice thickness model, we computed 10 m grids of ice thickness and bed topography that cover the entire ice cap. From these distributed datasets, we find that Jostedalsbreen (458 km2 in 2019) has a present (∼ 2020) mean ice thickness of 154 ± 22 m and an ice volume of 70.6 ± 10.2 km3. Locations of depressions in the map of bed topography are used to delineate potential future lakes, consequently providing a glimpse of the landscape if the entire Jostedalsbreen melts away. Together, the comprehensive ice thickness point values and ice-cap-wide grids serve as a baseline for future climate change impact studies at Jostedalsbreen. All data are available for download at https://doi.org/10.58059/yhwr-rx55 (Gillespie et al., 2024).

Guided and Space Waves Multiplexed Metasurface for Advanced Electromagnetic Functionalities in Microwave Region.

Nowadays, metasurfaces have attracted considerable attention due to their promising and advanced control of electromagnetic (EM) waves. However, it is still challenging to shape guided waves into desired free-space mode, while simultaneously manipulating spatial incident waves using a single metasurface. Herein, a class of metasurfaces capable of multiplexing guided and space waves is proposed to achieve advanced EM functionalities in microwave regions, which can find great application potentials in radar systems, wireless communications, and wireless power transfer (WPT). The proposed metasurface, composed of specially designed meta-atoms with polarization-dependent radiation and reflection properties, provides the capability to fully manipulate complex amplitude of guided waves and reflection phase of space incident wave independently and simultaneously, thus enabling arbitrary radiation and reflection functionalities without encountering crosstalk issues. As examples of potential applications, three advanced EM functionalities operating in both far-field and near-field regions are presented: low-sidelobe microwave antenna with reduced radar cross section (RCS), multifunctional WPT, and feed multiplexed holograms, respectively. The far-field characteristics of the low sidelobe level antennas showing radiated beams at ±30° together with RCS reduction under arbitrarily polarized incidences are validated by both simulations and measurements. A good agreement between experiments and simulations is also observed for the near-field intensity distribution of the hologram, which further validates the feasibility of near-field shaping. The findings significantly expand the capabilities of metasurfaces in manipulating EM waves and stimulate advanced multifunctional metadevices facing more challenging and diversified application demands.

Optimizing radar controlled airspace through ads-b implementation in Algerian aviation: the Northern FIR case

The Algerian Air Navigation Service Provider (ENNA) operates a surveillance network mostly relying on radar systems, leaving gaps in coverage in difficult terrain such as deserts and mountainous areas, thereby restricting traffic surveillance. Algerian airspace is mainly connected to Spanish and French airspace in the north, creating a natural link between Europe and Africa which demonstrates the impact of air traffic.ENNA's operations demand double continuous surveillance coverage of the airspace in northern Algeria characterized by high traffic in order to reinforce existing radar performance,fill coverage gaps and accommodate the growth of air traffic.The Automatic Dependent Surveillance Broadcast (ADS-B) system serves as a vital element of CNS/ATM advised by the International Civil Aviation Organization (ICAO) as the future of air traffic control solutions, offering numerous benefits in safety, cost and performance including large coverage in contrast to conventional surveillance systems, the ADS-B service significantly enhances traffic surveillance capabilities by more quickly updating and sharing accurate aircraft position data derived from satellite navigation, leading to better tracking abilities. These critical factors support the integration of ADS-B into Algerian airspace to address existing coverage deficiencies and traffic surveillance issues, thus leading to improved air traffic surveillance in northern Algeria. For this purpose, we propose an efficient and accurate coverage simulation to determine the best location and number of ADS-B receivers in order to achieve the most adequate ADS-B coverage possible to fully cover the northern Algerian airspace. The coverage of ADS-B can be ensured by comparison with current radar coverage.

A High-Resolution Spotlight Imaging Algorithm via Modified Second-Order Space-Variant Wavefront Curvature Correction for MEO/HM-BiSAR

A bistatic synthetic aperture radar (BiSAR) system with a Medium-Earth-Orbit (MEO) SAR transmitter and high-maneuvering receiver (MEO/HM-BiSAR) can achieve a wide swath and high resolution. However, due to the complex orbit characteristics and the nonlinear trajectory of the receiver, MEO/HM-BiSAR high-resolution imaging faces two major challenges. First, the complex geometric configuration of the BiSAR platforms is difficult to model accurately, and the ‘non-stop-go’ effects should also be considered. Second, non-negligible wavefront curvature caused by the nonlinear trajectories introduces residual phase errors. The existing spaceborne BiSAR imaging algorithms often suffer from image defocusing if applied to MEO/HM-BiSAR. To address these problems, a novel high-resolution imaging algorithm named MSSWCC (Modified Second-Order Space-Variant Wavefront Curvature Correction) is proposed. First, a high-precision range model is established based on an analysis of MEO SAR’s orbital characteristics and the receiver’s curved trajectory. Based on the echo model, the wavefront curvature error is then addressed by two-dimensional Taylor expansion to obtain the analytical expressions for the high-order phase errors. By analyzing the phase errors in the wavenumber domain, the compensation functions can be designed. The MSSWCC algorithm not only corrects the geometric distortion through reverse projection, but it also compensates for the second-order residual spatial-variant phase errors by the analytical expressions for the two-dimensional phase errors. It can achieve high-resolution imaging ability in large imaging scenes with low computational load. Simulations and real experiments validate the high-resolution imaging capabilities of the proposed MSSWCC algorithm in MEO/HM-BiSAR.

Validation of atmospheric evaporation duct in the eastern Indian Ocean

An atmospheric duct is an anomalous atmospheric structural phenomenon that causes trap refraction in the troposphere to change the propagation paths and ranges of electromagnetic waves, thereby increasing the detection distances of radar and other communications. Atmospheric ducts include evaporation, surface, and elevated ducts. Evaporation ducts are commonly found near the sea surface and can impact electromagnetic wave propagation, radar communication, and livelihood applications at low altitudes. The meteorological environment of the Indian Ocean is complex, and the characteristics of its evaporation duct are still poorly understood. We validate four select atmospheric duct models using the observed evaporation duct height (EDH) in the Indian Ocean and present their spatial as well as temporal characterizations in spring using in situ meteorological variables. The results show that the EDH derived using the Babin model has the lowest bias with the observed value; thus, the Babin model can be used by researchers in the future to study changes to the EDHs in sea areas with similar seasonal conditions. The EDH in the Indian Ocean has diurnal variations, with higher (lower) values during the daytime (nighttime). The EDH has a negative correlation with the relative humidity, and the standard deviation of the EDH is largest when the relative humidity is 90%. The EDH has the maximum value when the wind speed is in the range of 8–14 m/s and when the air–sea temperature difference is zero, i.e., ∆T=Tair−Tsea=0. This study validates four different EDH models in the Indian Ocean, thus broadening our knowledge on the tropical atmospheric boundary layer.

A Motion Compensation Method for Terahertz SAR Imaging with a Large Squint

Terahertz-band squint synthetic aperture radars (SARs) can obtain high-resolution images and have application potential in airborne radar systems. However, airborne radars usually have a large squint, which has led to traditional SAR algorithms no longer being applicable to airborne SARs. Additionally, terahertz radar imaging systems are more susceptible to the error induced by the platform’s motion. This paper proposes a motion compensation method for terahertz SAR imaging with a large squint angle. First, the signal model of motion compensation is derived, and the processing flow of imaging and motion compensation is detailed. Second, some simulations and experiments are conducted, and the results are reported. The results indicate that the proposed method can effectively correct the motion errors, and the signal model and processing flow are verified.

Viability of Substituting Handheld Metal Detectors with an Airborne Metal Detection System for Landmine and Unexploded Ordnance Detection

Commonly found landmines, such as the TM-62M, MON-100, and PDM-1, in the recent Russia–Ukraine war confirm the continued use of metals in munitions. Traditional demining techniques, primarily relying on handheld metal detectors and Ground Penetrating Radar (GPR) systems, remain state of the art for subsurface detection. However, manual demining with handheld metal detectors can be slow and pose significant risks to operators. Drone-based metal detection techniques offer promising solutions for rapid and effective landmine detection, but their reliability and accuracy remain a concern, as even a single missed detection can be life-threatening. This study evaluates the potential of an airborne metal detection system as an alternative to traditional handheld detectors. A comparative analysis of three distinct metal detectors for landmine detection is presented: the EM61Lite, a sensitive airborne metal detection system (tested in a pseudo-drone-based scenario); the CTX 3030, a traditional handheld all-metal detector; and the ML 3S, a traditional handheld ferrous-only detector. The comparison focuses on the number of metallic targets each detector identifies in a controlled test field containing inert landmines and UXOs. Our findings highlight the strengths and limitations of airborne metal detection systems like the EM61Lite and emphasize the need for advanced processing techniques to facilitate their practical deployment. We demonstrate how our experimental normalization technique effectively identifies additional anomalies in airborne metal detector data, providing insights for improved detection methodologies.

A moving-target imaging method for azimuth multi-channel HRWS SAR system based on spectrum energy distribution

ABSTRACT Azimuth multi-channel (AMC) synthetic aperture radar (SAR) systems can achieve high-resolution and wide-swath (HRWS) imaging, widely used in marine monitoring. However, for the moving ship targets irradiated by the AMC HRWS SAR system, false targets and defocus will appear in HRWS images caused by their motion. The existing methods behave poorly in case of low signal-to-noise ratio and channel non-uniformity. To improve the quality of HRWS images, the letter proposes a moving ship target imaging method based on spectrum energy distribution. Firstly, radial velocity of ship target is estimated by energy distribution factor parameter constructed by spectrum energy distribution. Secondly, the azimuth velocity is calculated by the phase difference between adjacent channels. Meanwhile, the importance of channel phase error on imaging is demonstrated. Finally, echo compensation and imaging method are performed to get a clear and focused image. Simulation experiments on point targets and area targets verify the effectivity of the proposed method. The proposed method can effectively suppress the false ship target, whose maximum energy is reduced from about −20 dB to below −40 dB, providing clearer images for the various application of different users.