Radar Mode Research Articles

Comparison of Stacked Sentinel‐3 A&B and AltiKa Repeat Cycle Data

AbstractSentinel‐3 A&B radar altimeters yield sea surface height measurements in both a high‐precision Synthetic Aperture Radar Mode (SARM), and a Pseudo‐Low Resolution Mode (PLRM). We stacked repeat cycles from both missions and in both modes to compare their resolution of small seamounts. Stacking entailed removing non‐geoidal heights and height errors, testing for consecutive measurements over ocean, aligning to common locations at 1 km intervals along a synthetic track, and forming a median height profile. These profiles are available from the National Centers for Environmental Information (NCEI) data repository. Global maps show that, over the oceans, the median height is usually derived from more than 49 cycles, and the typical error in an individual PLRM measurement is approximately 1.9 times greater than an individual SARM measurement. We applied a seamount detection bandpass filter to the median profiles and compared their spectral resolution to that of the Satellite for ARgos and AltiKa (SARAL) AltiKa mission. Small seamounts are similarly resolved by Sentinel‐3 A&B SARM data and by the SARAL/AltiKa data.

Radar Signal Intrapulse Modulation Recognition Based on a Denoising-Guided Disentangled Network

Accurate recognition of radar modulation mode helps to better estimate radar echo parameters, thereby occupying an advantageous position in the radar electronic warfare (EW). However, under low signal-to-noise ratio environments, recent deep-learning-based radar signal recognition methods often perform poorly due to the unsuitable denoising preprocess. In this paper, a denoising-guided disentangled network based on an inception structure is proposed to simultaneously complete the denoising and recognition of radar signals in an end-to-end manner. The pure radar signal representation (PSR) is disentangled from the noise signal representation (NSR) through a feature disentangler and used to learn a radar signal modulation recognizer under low-SNR environments. Signal noise mutual information loss is proposed to enlarge the gap between the PSR and the NSR. Experimental results demonstrate that our method can obtain a recognition accuracy of 98.75% in the −8 dB SNR and 89.25% in the −10 dB environment of 12 modulation formats.

Accelerated Holographic Imaging With Range Stacking for Linear Frequency Modulation Radar

General theory of holographic inversion with linear frequency modulation (GHI-LFM) has been proposed recently, providing the framework for further advances in the holographic methods for image reconstruction with millimeter-wave linear frequency modulation (LFM) radar. Here, accelerated holographic imaging (AHI)-LFM, an AHI method for LFM radar that exploits range stacking, is proposed. The method is developed and validated for the purpose of whole-body security screening. The image quality and the computational efficiency are compared with the original GHI-LFM algorithm. It is demonstrated that the AHI-LFM algorithm improves the reconstruction speed by at least an order of magnitude while preserving the same image quality for the image sizes arising in practical whole-body security screening.

RiwiSAR-SWH: A data-driven method for estimating significant wave height using Sentinel-3 SAR altimetry

More than 600 million people (about 10% of the world’s population) live in coastal areas that are less than 10 m above sea level. Despite the urgent need to monitor coastal waters, in situ measuring stations including wave buoys around the world do not provide sufficient insight into coastal water level variations, and in particular, they cannot provide sufficient information on one of the essential properties of water surfaces, namely the Significant Wave Height (SWH). Satellite altimetry plays an increasingly important role, especially after operating in Synthetic Aperture Radar (SAR) mode. However, due to the complexity of the coastal water surfaces, the performance of the satellite altimeters over the coastal area falls behind the open ocean surfaces. In addition, the well-known direct relationship between waveform rise time and SWH does not hold for SAR waveforms due to a different processing scheme. This study proposes a data-driven method to determine SWH using the Sentinel-3 data for both oceanic and coastal zones. For this purpose, we propose a method based on the rise time ( δ r ) and the width of a waveform, called RiwiSAR-SWH (rise time width model for SAR-SWH), which is free from the complexity of the SAR physical model and estimates SWH over the coastal area and open ocean in a relatively straightforward manner. We have employed our method over different regions in the coastal zone of the North Sea. The results are validated against in situ buoy data and compared with SWH estimates from SAMOSA+, SAMOSA++ and the Sentinel-3 Ocean retracker. The validation shows that the proposed method can determine SWH with accuracy ranging from 0.25 m to 0.91 m for different locations in the North Sea. Moreover, we obtain reliable SWH to within 1 km from the coast, which is an improvement of more than 40% compared to existing methodologies.

Experimental Evaluation of an Axillary Microwave Imaging System to Aid Breast Cancer Staging

The number of metastasised Axillary Lymph Nodes (ALNs) is a key indicator for breast cancer staging. Its correct assessment affects subsequent therapeutic decisions. Common ALN screening modalities lack high enough sensitivity and specificity. Level I ALNs produce detectable backscattering of microwaves, opening the way for Microwave Imaging (MWI) as a complementary screening modality. Radar-based MWI is a low-cost, non-invasive technique, widely studied for breast cancer and brain stroke detection. However, new specific challenges arise for ALN detection, which deter a simple extension of existing MWI methods. The geometry of the axillary region is more complex, limiting the antenna travel range required for maximum resolution. Additionally, unlike breast MWI setups, it is impractical to use liquid immersion to enhance energy coupling to the body; therefore, higher skin reflection masks ALNs response. We present a complete study that proposes dedicated imaging algorithms to detect ALNs dealing with the above constraints, and evaluate their effectiveness experimentally. We describe the developed setup based on a 3D-printed anthropomorphic phantom, and the antenna-positioning configuration. To the authors’ knowledge, this is the first ALN-MWI study involving a fully functional anatomically compliant setup. A Vivaldi antenna, operating in a monostatic radar mode at 2-5 GHz, scans the axillary region. Pre-clinical assessment in different representative scenarios shows Signal-to-Clutter Ratio higher than 2.8 dB and Location Error lower than 15 mm, which is smaller than considered ALN dimensions. Our study shows promising level I ALN detection results despite the new challenges, confirming MWI potential to aid breast cancer staging.

Target Localization Based on High Resolution Mode of MIMO Radar with Widely Separated Antennas

Coherent processing of multiple-input multiple-output (MIMO) radar with widely separated antennas has high resolution capability, but it also brings ambiguity in target localization. In view of the ambiguity problem, different from other signal processing sub-directions such as array configuration optimization or continuity of phase in space/time, this paper analyzes it from the information level, that is, the tracking method is adopted. First, by using the state equation and measurement equation, the echo data of multiple coherent processing intervals (CPI) are collected to improve the target localization accuracy as much as possible. Second, the non-coherent joint probability data association filter (JPDAF) is used to achieve stable tracking of spatial cross targets without ambiguity measurements. Third, based on the tracking results of the non-coherent JPDAF, the ambiguity of coherent measurement is resolved, that is, the coherent JPDAF is realized. By means of non-coherent and coherent alternating JPDAF (NCCAF) algorithms, high accuracy localization of multiple targets is achieved. Finally, numerical simulations are carried out to validate the effectiveness of the proposed NCCAF algorithm.

Radar Signal Recognition and Localization Based on Multiscale Lightweight Attention Model

The recognition technology of the radar signal modulation mode plays a critical role in electronic warfare, and the algorithm based on deep learning has significantly improved the recognition accuracy of radar signals. However, the convolutional neural networks became increasingly sophisticated with the progress of deep learning, making them unsuitable for platforms with limited computing resources. ResXNet, a novel multiscale lightweight attention model, is proposed in this paper. The proposed ResXNet model has a larger receptive field and a novel grouped residual structure to improve the feature representation capacity of the model. In addition, the convolution block attention module (CBAM) is utilized to effectively aggregate channel and spatial information, enabling the convolutional neural network model to extract features more effectively. The input time-frequency image size of the proposed model is increased to 600 × 600 , which effectively reduces the information loss of the input data. The average recognition accuracy of the proposed model achieves 91.1% at -8 dB. Furthermore, the proposed model performs better in terms of unsupervised object localization with the class activation map (CAM). The classification information and localization information of the radar signal can be fused for subsequent analysis.

An Extracting DEM Method Based on The Sub-apertures Difference in CSAR Mode

ABSTRACT This paper proposes a method based on the circular track synthetic aperture radar (CSAR) mode to directly obtain the digital elevation model (DEM) information of the target area through single-circle observation data. This paper improves and innovates the existing methods by using sub-aperture correlation. The circular motion trajectory of the entire radar observation platform is divided into multiple overlapping sub-aperture arcs. Each sub-aperture is projected in the height direction to observe the position deviation of the sub-aperture images more intuitively at different heights. Then, a new calculation method is used to calculate the correlation coefficient between sub-apertures, which enhances the accuracy of extracting DEM results. Finally, the measured data of the Ku band recorded by us are used to verify the effectiveness and accuracy of the algorithm proposed in this paper.

Improving Sentinel-3 SAR Mode Processing Over Lake Using Numerical Simulations

Access to fresh water is a key issue for the next decades in the context of global warming. The water level of lakes is a fundamental variable that needs to be monitored for this purpose. The radar altimetry constellation brings a worldwide means to this question. Recent advances in radar altimeter onboard tracking modes have allowed monitoring thousands of lakes and rivers. Now, measurements are widely available with better resolution: it is time to drastically improve the processing. The altimetry waveforms over lakes are difficult to analyze and very different from the ocean ones. We face a large variety of signals due to surface roughness, lake geometry, and environment. The inversion process, named retracking, shall be able to describe all these components. We propose here a retracking based on physical simulations taking as inputs the lake contour and the instrument characteristics. Fitting the simulation on the waveforms gives the water surface height. The algorithm has been tested on the Sentinel-3A and Sentinel-3B time series over Occitan reservoirs (France) and Swiss lakes and compared to <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">in situ</i> references. Over small Occitan reservoirs (few ha to few km <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> ), the unbiased root-mean-square error (ub-RMSE) is better than 14 cm. Over the medium-size Swiss lakes, the ub-RMSE is better than 10 cm for most of them.

Assessment of CryoSat-2 Baseline-D Height Product by GNSS and ICESat-2 in Lambert-Amery System, East Antarctica

CryoSat-2 repeatedly collects dense radar altimetry footprints covering high latitudes of the polar ice sheets for over ten years. The Baseline-D height product of CryoSat-2 was recently upgraded and released in 2019. Based on the internal or locally external evaluation of CryoSat-2 Baseline-D ice heights, we extended the validation both heterogeneously and spatially to accomplish a comprehensive assessment. First, reliable ice surface global navigation satellite system point solutions along the 36th Chinese National Antarctic Research Expedition traverse functioned as a height reference for comparison with the CryoSat-2 SAR synthetic aperture radar interferometric mode (SIN) data. Secondly, the Land Ice Along-Track Height product over Lambert&#x2013;Amery system (LAS) from ice, cloud, and land elevation satellite 2 (ICESat-2), was also applied to validate CryoSat-2 SIN and low-resolution mode (LRM) data. As the results indicate, the SIN height accuracy is evaluated to be &#x2212;1.68 m &#x00B1; 2.35 m (slope &lt; 0.65&#x00B0;) along the traverse and &#x2212;0.96 &#x00B1; 1.95 m (slope &lt; 0.95&#x00B0; and roughness &lt; 3 m) over the margin of LAS. The LRM height accuracy is evaluated to be &#x2212;0.13 &#x00B1; 0.46 m (slope &lt; 0.1&#x00B0; &amp; roughness &lt; 1 m) over the interior of LAS. The standard deviation of the height differences degrades linearly against the limited growth of the terrain slope&#x002F;roughness at the confidence level of 99&#x0025;. It is worth noting that the spatially heterogeneous pattern of height differences is correlated with surface topography variations. This article should imply the potential to improve the estimation of mass balance and its uncertainty of polar ice sheets based on radar altimetry data.

Multifunctional Radar Cognitive Jamming Decision Based on Dueling Double Deep Q-Network

To solve the inefficient and imprecise problem using the Deep Q-network (DQN) algorithm for the radar jamming decision, this paper proposes a multifunctional radar jamming decision optimization method based on the Dueling Double Deep Q-network (D3QN). First, we use a value function reflecting the radar state’s change, and an advantage function related to radar state S and jamming action A to improve the cognitive jamming level for unknown radar modes. Then, using the dueling networks for jamming strategy selection and effectiveness evaluation can further improve decision accuracy. Finally, we propose a prioritized experience replay mechanism during network training to shorten the decision-making time. The experimental results show that our proposed method completes decision tasks 2.1 times more efficiently than the DQN and improves decision accuracy by approximately 10% over DQN.

Improving the accuracy of measurement range and speed air target radar mode medium pulse repetition frequency by estimation the signal level of background returns

Improving the accuracy of measurement range and speed air target radar mode medium pulse repetition frequency by estimation the signal level of background returns

Performances of the Passive SAR Imaging of Jupiter’s Icy Moons

With the development of the JUICE/RIME (ESA) and Europa-Clipper/REASON (NASA) instruments, designed to study the subsurface of the Galilean moons, interest has been growing to study the performances of sounding radar orbiting these bodies. In the presence of strong Jupiter’s radio emissions, probing in a passive mode using these emissions as the emitter is considered. However, radar performances in this bistatic mode are dependent on the entire geometry of observation: the position of the source of emission, the spacecraft trajectory, and on the region probed. 3D Simulations are necessary to estimate the performances of these measurements. We analyze the influence of the geometry of observation by approximating Jovian radio bursts as radio impulses, simulating the signal scattered by a point target in a realistic 3D geometry and computing the resolution. This allows a preliminary identification of scenarios of observation best suited for this radar mode. The influence of the correct localization of Jupiter’s emissions on the SAR image is investigated as well, and interest in recovering the true position of Jupiter’s source is highlighted.

A Truncated Matched Filter Method for Interrupted Sampling Repeater Jamming Suppression Based on Jamming Reconstruction

Interrupted sampling repeater jamming (ISRJ) is becoming more widely used in electronic countermeasures (ECM), thanks to the development of digital radio frequency memory (DRFM). Radar electronic counter-countermeasure (ECCM) is much more difficult when the jamming signal is coherent with the emitted signal. Due to the intermittent transmission feature of ISRJ, the energy accumulation of jamming on the matched filter shows a ‘ladder’ characteristic, whereas the real target signal is continuous. As a consequence, the time delay and distribution of the jamming slice can be obtained based on searching the truncated-matched-filter (TMF) matrix. That is composed of pulse compression (PC) results under matched filters with different lengths. Based on the above theory, this paper proposes a truncated matched filter method by the reconstruction of jamming slices to suppress ISRJ of linear frequency modulation (LFM) radars. The numerical simulations indicate the effectiveness of the proposed method and validate the theoretical analysis.

Specific features of immunity control of survey radar under its suppression by active interference and interfering information effects

The features of goal-setting control while ensuring the information stability of the sounding modes of a surveillance radar when it is suppressed by active interference and interfering information influences are considered. Overcoming the complexity of goal-setting processes, the validity and efficiency of decision-making with a shortage of time for its adoption is associated with insuring the consistency of goal-setting processes, increasing the levels of their intellectualization and formalization. This will contribute to imparting the desired properties, synthesized during the conflict, to the multipurpose strategies and the situational law of the control of the REP processes and the coordination of actions.&#x0D; An increase in the level of intellectualization of goal-setting processes is ensured by:&#x0D; - decomposition of the general goal-setting problem into separate, simpler subtasks with effective solutions, implemented in the corresponding subsystems of the ACSstab (or basic associations of its functional elements) at stages of information support, preparation, adoption and implementation of the decision at the stages of hierarchical levels of management;&#x0D; - cognitive analysis of goals and reflexive synthesis of goal-setting processes using the capabilities of a specialized intelligent decision support system to enhance the creative-reflexive abilities of the subject of management and increase the level of his professional competencies;&#x0D; - combining the universality of the stages of rational management of the synthesis of the strategy for managing the REP processes with the specifics of conflict situations, subjectivity, cognition and reflexivity nature of intellectual control.&#x0D; Methods and means for partial formalization of goal-setting processes are presented, when the structuring of the main goal is carried out taking into account belonging to the strategies of internal and external control of the REP, the decomposition of the two-sided dynamic model of the conflict between the systems of the RES complex and the radar, the hierarchy of management levels, various approaches applied to goal-setting in a crisis management, as well as methods of justifying goals, resource costs and control of achieving the goals.&#x0D; These features can significantly reduce the degree of subjectivity of management for goal-setting and achieve their validity, completeness, consistency.

Peculiarities of purpose in providing the information stability of surveillance radar sensing modes in the process of their radio electronic suppression

It is possible to look at the special features of the goal setting while ensuring information stability of radar sounding modes when they are suppressed by the active interferences and interfering information influences. Overcoming the complexity of goal-setting processes, the validity and prompt decision-making with a shortage of time for its adoption is associated with insuring the consistency of goal-setting the levels of their intellectualization and formalization. This will contribute to imparting the desired properties, synthesized during the conflict, to the multipurpose strategies and the situational law of the control of the REP processes and the coordination of actions. An increase in the level of intellectualization of goal-setting processes is ensured by: decomposition of the general goal-setting problem into separate, simpler subtasks with effective solutions, implemented in the corresponding subsystems of the ACSstab (or basic associations of its functional elements) at stages of information support, preparation, adoption and implementation of the decision at the stages of hierarchical levels of management; cognitive analysis of goals and reflexive synthesis of goal-setting processes using the capabilities of a specialized intelligent decision support system to enhance the creative-reflexive abilities of the subject of management and increase the level of his professional competencies; combining the universality of the stages of rational management of the synthesis of the strategy for managing the REP processes with the specifics of conflict situations, subjectivity, cognition and reflexivity nature of intellectual control. Methods and means of partial formalization of goal-setting processes are presented, when the structuring of the main goal is carried out taking into account belonging to the strategies of internal and external control of the REP, the decomposition of the two-sided dynamic model of the conflict between the systems of the RES complex and the radar, the hierarchy of management levels, various approaches applied to goal-setting in a crisis management, as well as methods of justifying goals, resource costs and control of achieving the goals. These features can significantly reduce the degree of subjectivity of management for goal-setting and achieve their validity, completeness, consistency.

Characteristic Parameter Optimization of Wireless Flaw Sensing System Based on Active Interference Suppression Algorithm

Based on the active interference suppression algorithm, this study combines the radar working mode and the interference type and realizes the effective detection of the flaw detection signal by successively processing the radar receiving signal and the filtering processing. Firstly, this article builds a simulation platform similar to the actual situation to verify the existing conventional active interference suppression algorithms. Secondly, for the detection of chirp active deception jamming signals entering from the main lobe, a radar active deception jamming detection method based on the characteristic parameter matching of the harmonic components of active deception jamming signals is proposed. After that, the spectral characteristics of the harmonic components of the deception interference signal are analyzed, and the center frequency and the tuning frequency of the real target echo are obtained. Finally, by establishing a frequency modulation parameter library for possible interference harmonic signal components, the acquisition phase of the radar gate by the jammer matched analysis with the preestablished frequency modulation parameter library is implemented to achieve active deception interference detection. This method can effectively detect active deception jamming signals in a complex tunnel environment. The interference suppression algorithms verified by simulation include noise FM interference suppression algorithm based on cancellation and distance false target interference suppression algorithm based on LFM radar summary processing. Through actual measurement data processing and analysis, the effectiveness of the method is verified and the idea of interference suppression is expanded. The construction of the simulation platform is obtained by appropriately modifying the actual parameters, a certain type of suppression jammer, and a certain type of deception jammer used in a certain countermeasure field test at a radar station.

Radar Signal Modulation Recognition Based on Sep-ResNet.

With the development of signal processing technology and the use of new radar systems, signal aliasing and electronic interference have occurred in space. The electromagnetic signals have become extremely complicated in their current applications in space, causing difficult problems in terms of accurately identifying radar-modulated signals in low signal-to-noise ratio (SNR) environments. To address this problem, in this paper, we propose an intelligent recognition method that combines time–frequency (T–F) analysis and a deep neural network to identify radar modulation signals. The T–F analysis of the complex Morlet wavelet transform (CMWT) method is used to extract the characteristics of signals and obtain the T–F images. Adaptive filtering and morphological processing are used in T–F image enhancement to reduce the interference of noise on signal characteristics. A deep neural network with the channel-separable ResNet (Sep-ResNet) is used to classify enhanced T–F images. The proposed method completes high-accuracy intelligent recognition of radar-modulated signals in a low-SNR environment. When the SNR is −10 dB, the probability of successful recognition (PSR) is 93.44%.

A synergic method of Sentinel-1 and Sentinel-2 images for retrieving soil moisture content in agricultural regions

Remote sensing techniques, which provide timely and accurate soil moisture information to improve food production, are becoming increasingly popular among agricultural production in China and many other regions. It also shows its importance in monitoring agricultural basins where the meteorological and topographic conditions vary greatly. In this case, the reliability of soil moisture content (SMC) monitoring for theses basins could be promised. The main objective of this paper is to develop a synergic method of radar and optical data, as well as an on-site sampling scheme, to accurately estimate SMC in the basin. The reason is that in the winter wheat production area of Dawen River basin in China, there are few conventional SMC testing equipment. Considering the characteristics of different crops and the conditions of crops in different growth periods, the VV polarization mode of Sentinel-1 C-band Synthetic Aperture Radar (SAR) images was used to retrieve SMC. Combined with the Normalized difference vegetation index (NDVI) extracted from Sentinel-2 MSI optical images and the optimized Water Cloud Model (WCM), the surface backscattering coefficient was obtained by eliminating vegetation moisture content (VMC), and the SMC model was established. The results showed that from March to May in 2020, the coefficient of determination (R2) between the estimated VMC and the field observation was 0.655, and the Root Mean Square Error (RMSE) between the two was 0.334. In the inversion algorithm model, the R2 between the retrieved SMC and the field measurement was 0.506, and the RMSE was 3.725.

Joint waveform design of cognitive radar based on LSTM network in the presence of signal-dependent interference

Waveform design is a key component of cognitive radar. However, waveforms designed using a single criterion have difficulty meeting the multi-working mode of radar. We present a joint waveform design method in the presence of signal-dependent interference based on a long short term memory network. The proposed method combines characteristics of mutual information (MI) and signal to interference-plus-noise-ratio (SINR) criteria and achieves a smooth trade-off between them. The minimum mean square error (MMSE) method is set as a comparison to prove the enhanced capabilities in detection and recognition. Here, we initiate a final recognition rate indicator of radar to measure the radar’s comprehensive performance. As a result, compared with the MI criterion, SINR criterion, and MMSE method, to use as a transmission signal, the proposed paradigm increased the final recognition rate by 4.08%, 6.89%, and 5.25%, respectively, verifying the effectiveness of the proposed method.