Radar Model Research Articles

Performance evaluation of a state-of-the-art automotive radar and corresponding modeling approaches based on a large labeled dataset

Radar is a key sensor to achieve a reliable environment perception for advanced driver assistance system and automated driving (ADAS/AD) functions. Reducing the development efforts for ADAS functions and eventually enabling AD functions demands the extension of conventional physical test drives with simulations in virtual test environments. In such a virtual test environment, the physical radar unit is replaced by a virtual radar model. Driving datasets, such as the nuScenes dataset, containing large amounts of annotated sensor measurements, help understand sensor capabilities and play an important role in sensor modeling. This article includes a thorough analysis of the radar data available in the nuScenes dataset. Radar properties, such as detection thresholds, and detection probabilities depending on object, environment, and radar parameters, as well as object properties, such as reflection behavior depending on object type, are investigated quantitatively. The overall detection probability of the considered radar (Continental ARS-408-21) was found to be 27.81%. Four radar models on object level with different complexity levels and different parametrisation requirements are presented: a simple RCS-based radar model with an accuracy of 51%, a linear SVC model with an accuracy of 70%, a Random Forest model with an accuracy of 83%, and a Gradient Boost model with an accuracy of 86%. The feature importance analysis of the machine learning algorithms revealed that object class, object size, and object visibility are the most important parameters for the presented radar models. In contrast, daytime and weather conditions seem to have only minor influence on the modeling results.

Monitoring crop growth using a canopy structure dynamic model and time series of synthetic aperture radar (SAR) data

ABSTRACT Normalized Difference Vegetation Index (NDVI) time series data are used by agricultural agencies for many essential operational crop monitoring programmes. But optical sensors often miss key growth stages due to cloud cover interference, impacting the performance of operational activities. Although the synergistic use of optical and Synthetic Aperture Radar (SAR) imagery can provide time series data, any SAR-optical integration necessitates building a relationship between these two data sources. The objective of this study was to use a semi-empirical Canopy Structure Dynamics Model (CSDM), Growing Degree Days (GDD), and SAR parameters calibrated to optical NDVI to derive daily estimates of canola crop condition over an entire growing season. RADARSAT-2 Fine Quad-pol and RapidEye images were collected over three years for a study site in western Canada. Object-based image analysis was applied to study the relationship between the optical and SAR time series data. Significant correlations were documented between a number of SAR parameters and optical NDVI, specifically a ratio of backscatter intensities (HH-HV)/(HH+HV), a ratio of volume to surface scattering extracted from the Freeman Durden decomposition, and Entropy from the Cloude-Pottier decomposition. Correlations (r-values) between these SAR parameters and optical NDVI ranged from 0.63 to 0.84 for the three years of data. Based on this analysis, a simple statistical model was used to relate SAR parameters to optical NDVI, creating a SAR-calibrated NDVI (SARcal-NDVI). A CSDM was fit to the SARcal-NDVI for each canola field, constructing a temporal vegetation index curve which captured canopy development from emergence to senescence. Coefficients of determination (R2) were 0.87 0.86 and 0.82 for entropy, the volume-surface scattering ratio, and the ratio of backscatter intensities (HH-HV)/(HH+HV), respectively, demonstrating a good model fit. The CSDM describes well the temporal evolution of SARcal-NDVI. Using the CSDM, SARcal-NDVI and GDD, the canola condition can be estimated for any given day in the growing season. In fact when the CSDM was used to estimate SARcal-NDVI for the exact days of RapidEye acquisitions, correlations with optically derived NDVI were high. The strongest correlations with RapidEye NDVI were reported for the volume-surface scattering ratio (R2 of 0.69 and RMSE of 0.15). The SARcal-NDVI estimated from the CSDM was also physically meaningful. Field-based biomass was significantly correlated (R2 of 0.79) with the SARcal-NDVI calculated using the volume-surface scattering ratio. Although further research is needed to extend this method to other crops, these results demonstrate that SAR data can be used to estimate vegetation conditions and when coupled with a CSDM, integrated into current monitoring operations based on optical NDVI. As a next step, the research team will be assessing SARcal-NDVI in a national operational programme which reports on crop yields using modelling with optical-based NDVI.

Tracking the invasive hornet Vespa velutina in complex environments by means of a harmonic radar

An innovative scanning harmonic radar has been recently developed for tracking insects in complex landscapes. This movable technology has been tested on an invasive hornet species (Vespa velutina) for detecting the position of their nests in the environment, in the framework of an early detection strategy. The new model of harmonic radar proved to be effective in tracking hornets either in open landscapes, hilly environments and areas characterised by the presence of more obstacles, such as woodlands and urban areas. Hornets were effectively tracked in complex landscapes for a mean tracking length of 96 ± 62 m with maximum values of ~ 300 m. The effectiveness of locating nests was 75% in new invasive outbreaks and 60% in highly density colonised areas. Furthermore, this technology could provide information on several aspects of insect’s ecology and biology. In this case, new insights were obtained about the mean foraging range of V. velutina (395 ± 208 m with a maximum value of 786 m) and flying features (ground speed), which was 6.66 ± 2.31 m s−1 for foraging individuals (hornets that are not carrying prey’s pellet) and 4.06 ± 1.34 m s−1 for homing individuals.

Adaptive digital self-interference cancellation based on fractional order LMS in LFMCW radar

Adaptive digital self-interference cancellation (ADSIC) is a significant method to suppress self-interference and improve the performance of the linear frequency modulated continuous wave (LFMCW) radar. Due to efficient implementation structure, the conventional method based on least mean square (LMS) is widely used, but its performance is not sufficient for LFMCW radar. To achieve a better self-interference cancellation (SIC) result and more optimal radar performance, we present an ADSIC method based on fractional order LMS (FOLMS), which utilizes the multi-path cancellation structure and adaptively updates the weight coefficients of the cancellation system. First, we derive the iterative expression of the weight coefficients by using the fractional order derivative and short-term memory principle. Then, to solve the problem that it is difficult to select the parameters of the proposed method due to the non-stationary characteristics of radar transmitted signals, we construct the performance evaluation model of LFMCW radar, and analyze the relationship between the mean square deviation and the parameters of FOLMS. Finally, the theoretical analysis and simulation results show that the proposed method has a better SIC performance than the conventional methods.

Microphysical and Polarimetric Radar Modeling of Hydrometeor Refreezing

AbstractA unique polarimetric radar signature indicative of hydrometeor refreezing during ice pellet events has been documented in several recent studies, yet the underlying microphysical causes remain unknown. The signature is characterized by enhancements in differential reflectivity (ZDR), specific differential phase (KDP), and linear depolarization ratio (LDR), and a reduction in copolar correlation coefficient (ρhv) within a layer of decreasing radar reflectivity factor at horizontal polarization (ZH). In previous studies, the leading hypothesis for the observed radar signature is the preferential refreezing of small drops. Here, a simplified, one-dimensional, explicit bin microphysics model is developed to simulate the refreezing of fully melted hydrometeors, and coupled with a polarimetric radar forward operator to quantify the impact of preferential refreezing on simulated radar signatures. The modeling results demonstrate that preferential refreezing is insufficient by itself to produce the observed signatures. In contrast, simulations considering an ice shell growing asymmetrically around a freezing particle (i.e., emulating a thicker ice shell on the bottom of a falling particle) produce realistic ZDR enhancements, and also closely replicate observed features in ZH, KDP, LDR, and ρhv. Simulations that assume no increase in particle wobbling with freezing produce an even greater ZDR enhancement, but this comes at the expense of reducing the LDR enhancement. It is suggested that the polarimetric refreezing signature is instead strongly related to both the distribution of the unfrozen liquid portion within a freezing particle and the orientation of this liquid with respect to the horizontal.

One Health EJP - RaDAR model inventory: a user-friendly tool for annotating and exchanging models

The lack of a harmonized model exchange formats among modelling tools impedes communication between researchers, since the exchange and usage of existing models in various software environments can be very difficult. The RaDAR model inventory aims to provide a platform to exchange models among professionals utilizing the Food Safety Knowledge Exchange (FSKX) Format (de Alba Aparicio et al. 2018) as a harmonized model exchange format. FSKX defines a framework that encodes all relevant data, metadata, and model scripts in an exchangeable file format. However, the creation of such a file can be a time-consuming and difficult process. To increase the usage of the FSK standard, we developed the RaDAR model inventory web application that targets the process of creating an FSKX file for the end user. Our inventory aims to be a user-friendly tool that allows users to create, read, edit, write, execute and compile FSKX files within the web browser. The possibility of sharing models with the public or a specific group of people facilitates collaboration and the exchange of information. Since the RaDAR model inventory is based on the open-source technology of Project Jupyter (Granger and Perez 2021), it can support nearly all relevant programming languages executed within a reproducible cloud-computing environment. The intuitive nature of the RaDAR model along with its wide range of features reduce the threshold for contribution to a harmonized model exchange format and eases collaboration. The RaDAR model inventory can be accessed at http://ejp-radar.eu.

Adopting and implementing an innovative model to organize diabetes care within First Nations communities: A qualitative assessment

BackgroundDiabetes care remains suboptimal in First Nations populations. Innovative and culturally relevant approaches are needed to promote systematic and proactive organization of diabetes care for people living with diabetes on-reserve in Canada. The RADAR model is one strategy to improve care: an integrated disease registry paired with an electronic health record for local community healthcare providers with remote care coordination. We qualitatively assessed adoption and implementation of RADAR in First Nations communities in Alberta to inform its potential spread in the province.MethodsWe used the RE-AIM framework to evaluate adoption and implementation of RADAR in 6 First Nations communities. Using purposeful sampling, we recruited local healthcare providers and remote care coordinators involved in delivering RADAR to participate in telephone or in-person interviews at 6- and 24-months post-implementation. Interviews were digitally recorded, transcribed, and verified for accuracy. Data was analyzed using content analysis and managed using ATLAS.ti 8.ResultsIn total, we conducted 21 semi-structured interviews (6 at 6-months; 15 at 24-months) with 11 participants. Participants included 3 care coordinators and 8 local healthcare providers, including registered nurses, licensed practical nurses, and registered dietitians. We found that adoption of RADAR was influenced by leadership as well as appropriateness, acceptability, and perceived value of the model. In addition, we found that implementation of RADAR was variable across communities regardless of implementation supports and appropriate community-specific adaptations.ConclusionsThe variable adoption and implementation of RADAR has implications for how likely it will achieve its anticipated outcomes. RADAR is well positioned for spread through continued appropriate community-based adaptations and by expanding the existing implementation supports, including dedicated human resources to support the delivery of RADAR and the provision of levels of RADAR based on existing or developed capacity among local HCPs.Trial registrationNot applicable to this qualitative assessment. ISRCTN14359671.

RCS 모의 데이터를 활용한 기동에 따른 레이다 성능 분석

During radar operation, changes in the radar cross section (RCS) of a target have an adverse effect on the radar detection performance. In particular, the RCS of a target with high maneuvering characteristics can be changed rapidly. Therefore, a precise prediction of the RCS change is essential for satisfactory radar detection performance. In this study, a modeling and simulation (M&S) tool was developed for the estimation of radar detection performance. The M&S tool comprises a radar model, target model, and wave propagation model. In particular, pre-obtained RCS simulation data were utilized to consider the effect of the RCS change of the target. Using the developed tool, the RCS based on the relative attitude is extracted from the RCS simulation data and the RCS processed data using the moving average method. The M&S model is verified by comparing the two test results with the radar received signal power. Consequently, we verified that when using the RCS manufacturing data, the signal power is more similar to the test data than the other RCS simulation methods. It is expected that the radar performance on the high-maneuvering target can be estimated using the developed M&S tool.

New modeling method of millimeter-wave radar considering target radar echo intensity

Virtual test evaluation is an important development direction for automatic driving technology testing and evaluation. The millimeter-wave radar sensor model used in virtual test evaluation should meet the real-time and accuracy requirements of the system. The current millimeter-wave radar model can satisfy real-time requirements but cannot simulate the physical characteristics of millimeter-wave radar. This study proposes a millimeter-wave radar model, which introduces the radar cross-sectional (RCS) area judgment index based on geometric clipping extraction and target visibility judgment. Through simulation verification of target visibility, the millimeter-wave radar model integrated with RCS indicators has demonstrated consistent test results with real millimeter-wave radar. The millimeter-wave radar model can better simulate the physical characteristics and error conditions of real millimeter-wave radar as well as enhance the accuracy of virtual simulation tests and evaluation of automatic driving while ensuring the real-time requirements of the simulation.

Deformation Retrieval Using the Spatially Constrained MTInSAR Method

The observation model of multitemporal inteferometric synthetic aperture radar (MTInSAR) is an underdetermined system. To obtain a unique solution, the traditional techniques impose the temporal constraints by assuming the deformation pattern typically as, e.g., a linear or polynomial model. However, these temporal constraints are not necessarily compatible with the realistic deformation, especially for complex deformations of, e.g., landslides and permafrost. Such discrepancy will bias the retrieval of MTInSAR parameters, thus producing inaccurate deformation results. In this letter, we propose a method for directly solving the deformation sequence by imposing the spatial similarity constraints instead of temporal constraints. The underlying rationale is that the spatially closer points share more similar deformation patterns for most motion events. The capability of the proposed method for retrieving displacement is initially demonstrated by using both simulated and real data experiments.

An Improved and Novel Approach for Frequency Domain Forward Modeling of GPR Data Using the Finite Difference Staggered Grid Technique

Forward modeling of ground penetrating radar (GPR) data is important for understanding relationships between dielectric layers. For the inversion of GPR data, an effective and advanced forward modeling scheme is always desirable. Here, staggered grid formulations for the finite difference frequency domain (FDFD) method have been developed and modified for the forward modeling of GPR data. The forward problem is first solved using a nine-point regular staggered grid that basically approximates and discretizes the Laplacian operator. In the case of transverse electric mode FDFD method, the implementation of a perfectly matched layer (PML) has been shown to be effective. Among the several PML techniques, the complex frequency shifted perfectly matched layer method has proven to be most useful for absorbing evanescent waves. In this paper, a new and improved nine-point mixed staggered grid formulation is proposed by considering the combination of a five-point Cartesian and nine-point rotated staggered grid. The derived stencils are compared after estimating the reflection errors from the computed simulated wavefields ( $${E}_{y}$$ ) of the homogeneous subsurface model. This newly developed technique exhibits less error than the regular and unstaggered mixed stencils. Lastly, this better and less-time consuming grid is used to extract GPR data from realistic sedimentary models with a surface acquisition setup.

Two-Dimensional DOA Estimation of MIMO Radar Coherent Source Based on Toeplitz Matrix Set Reconstruction

In order to realize the high-precision direction of arrival (DOA) estimation of the coherent source of two-dimensional multiple-input and multiple-output (MIMO) radar, a solution is given by combining Toeplitz matrix set reconstruction. MIMO radar obtains a larger aperture with fewer arrays. Traditional two-dimensional reconstruction Toeplitz-like algorithms use part of the information in the construction of two correlation matrices or covariance matrices to construct the Toeplitz matrix when performing two-dimensional coherent source DOA estimation, which makes the information utilization incomplete and requires additional denoising processing. To solve the above problems, this paper proposes an improved Toeplitz matrix set reconstruction algorithm based on the two-dimensional reconstruction Toeplitz class algorithm. The complete array element receiving signal vector is used to construct two Toeplitz matrix sets containing complete information, and then their conjugate transposes. Multiply and sum to correct the matrix to obtain a full-rank matrix, so as to achieve the purpose of decoherence and combine the traditional ESPRIT algorithm to perform two one-dimensional reconstruction processing through rotation invariance and then perform angle matching to achieve two-dimensional coherent signal angle estimation, while avoiding additional denoising processing. Finally, the simulation results of the cross array and the L-shaped array verify the effectiveness of the algorithm in this paper and further extend it to the two-dimensional MIMO radar array model and compare it with the traditional ESPRIT-like algorithm and the REC-FBSS-ESPRIT algorithm. In comparison, the algorithm in this paper has better performance under the conditions of successful resolution, DOA estimation accuracy, and low signal-to-noise ratio.

Pattern Synthesis of MIMO Radar Based on Immune Differential Evolution Algorithm

In order to optimize the pattern synthesis of multiple input and multiple output (MIMO) radar, immune mechanism is adopted to overcome the premature risk of differential evolution (DE) algorithm, namely immune differential evolution (IDE). Firstly, the modeling of MIMO radar is introduced by encoding the position of array in the binary. Secondly, the immune mechanism is employed to improve the DE. In IDE, two parameters are self-adapted for the mutation operator by immune mechanism to enhance the convergence ability of DE, including scaling factor and crossover rate. Several experiments are conducted to analysis the performance of IDE. The simulation results show that the IDE with variable parameters can get optimal results in MIMO radar with lower the peak side-lobe level (PSLL) and maintain the diversity with stronger convergence ability and shorter calculation speed.

Using Microwave Profile Radar to Estimate Forest Canopy Leaf Area Index: Linking 3D Radiative Transfer Model and Forest Gap Model

Profile radar allows direct characterization of the vertical forest structure. Short-wavelength, such as Ku or X band, microwave data provide opportunities to detect the foliage. In order to exploit the potential of radar technology in forestry applications, a helicopter-borne Ku-band profile radar system, named Tomoradar, has been developed by the Finnish Geospatial Research Institute. However, how to use the profile radar waveforms to assess forest canopy parameters remains a challenge. In this study, we proposed a method by matching Tomoradar waveforms with simulated ones to estimate forest canopy leaf area index (LAI). Simulations were conducted by linking an individual tree-based forest gap model ZELIG and a three-dimension (3D) profile radar simulation model RAPID2. The ZELIG model simulated the parameters of potential local forest succession scene, and the RAPID2 model utilized the parameters to generate 3D virtual scenes and simulate waveforms based on Tomoradar configuration. The direct comparison of simulated and collected waveforms from Tomoradar could be carried out, which enabled the derivation of possible canopy LAI distribution corresponding to the Tomoradar waveform. A 600-m stripe of Tomoradar data (HH polarization) collected in the boreal forest at Evo in Finland was used as a test, which was divided into 60 plots with an interval of 10 m along the trajectory. The average waveform of each plot was employed to estimate the canopy LAI. Good results have been found in the waveform matching and the uncertainty of canopy LAI estimation. There were 95% of the plots with the mean relative overlapping rate (RO) above 0.7. The coefficients of variation of canopy LAI estimates were less than 0.20 in 80% of the plots. Compared to lidar-derived canopy effective LAI estimation, the coefficient of determination was 0.46, and the root mean square error (RMSE) was 1.81. This study established a bridge between the Ku band profile radar waveform and the forest canopy LAI by linking the RAPID2 and ZELIG model, presenting the uncertainty of forest canopy LAI estimation using Tomoradar. It is worth noting that since the difference of backscattering contribution is caused by both canopy structure and tree species, similar waveforms may correspond to different canopy LAI, inducing the uncertainty of canopy LAI estimation, which should be noticed in forest parameters estimation with empirical methods.

Research and Implementation of Emitter Threat Assessment Based on Distributed Simulation

Abstract The threat degree of radiation source detected by fighter in penetration operation is the main reference for fighter to make the next operation plan. The research objective of this project is to evaluate the threat of radiation sources detected by aircraft, based on distributed interactive simulation technology, the system modeling of aircraft flight detection data and ground radar detection warning in distributed system is realized by building a variety of simulation modules such as ground radar model, aircraft radar model, coordinate transformation model and threat level evaluation model, the simulation environment system of airborne emitter warning is completed. In this experimental environment, through simulation, the real-time calculation of the threat factor of the aircraft radiation source can be carried out, and then the dynamic threat assessment of the radiation source target can be realized.

Model of radar station functioning in energy potential instability conditions

The energy potential of the radar is evaluated at the stage of testing when accompanied by reference spacecraft-calibration spheres. At the same time, special attention is paid to the readiness and serviceability of the radar equipment for conducting measurements and providing tests with high-precision data on the position in space and the effective scattering area (ESA) of the reference spacecraft. However, during the normal operation of the radar, it is often not possible to provide such conditions – the state of the radar equipment during measurements is constantly changing, and the limited number of calibration spheres in orbit does not allow measurements to be carried out with sufficient frequency. At the same time, in the radar field of view, there are constantly associated spacecraft for various purposes, measurements of the trajectory parameters of which can be used to assess the energy potential of the radar in real time. When making such measurements, it is necessary to take into account the actual state of the radar equipment and the fluctuations of the signal reflected from the spacecraft of complex shape. The presented model describes the factors that affect the instability of the energy potential during the operation of the radar in real operating conditions when accompanied by associated spacecraft, and allows us to identify the most significant of them. Currently, there are radar models that take into account the features of tracking space objects when changing the conditions for the propagation of electromagnetic waves in space, maneuvering targets, when observing targets against the background of interference, and others. At the same time, the combination of changes in the energy parameters of the radar and the reflected signal in these models was not fully considered. The need to create a model for the operation of a radar station in conditions of instability of the energy potential is also due to the development of technologies for creating small-sized spacecraft, the main distinguishing feature of which is the low radar visibility for stations in the decimeter range. As the ESA decreases, the power of the signal received by the antenna decreases, which increases the relative measurement error and increases the probability of a false target miss. Small-sized spacecraft are understood to be spacecraft with linear dimensions of the order of 0,1x0,1x0,1 m. The ESA of such objects varies in the range from a few hundredths to units of square meter σэф = (0,01…4) m2.

Innovation Radar for Disruptive Technology Insertion: The Case of Autonomous Vehicles in Brazil and France

This paper seeks to identify the critical success factors, to propose a theoretical model of the innovation radar for the insertion of autonomous vehicles as a product-service system in a country, and to map and discuss the radar in the context of Brazil and France. Fundamentally, it seeks to address the gap between the development of AVs, the differences between two national contexts, and the lack of specific knowledge about how to manage disruptive innovation in countries. From the results, the intent is to clear diagnosis about the innovation, allowing the formulation of guidelines and actions for the capacity development of a country. The results obtained in Brazil and France were crossed with official data and statistics as a way to corroborate the use of the innovation radar as a tool.

Security multi-position radar systems: model, topology, structure

In accordance with the general ideas about the relevance, methods and means of protecting important protected objects, as well as the principles of constructing single and multi-position radar systems (radar), the features of radar perimeter protection are considered, with the presentation of it as a large hierarchical system of interconnected, united by a common purpose of functioning controlled subsystems. The measured radar parameters, advantages and disadvantages of security radars, as well as the advantages of multi-position radars over single-position ones are noted. The elements of a mathematical model of a multi-position radar are presented, for which: decomposition of technical protection as a large system; the features of the matrix-vector description of the parameters of the generated and received radar signals of a multi-position radar are considered; analyzed the topology of the security radar as a single object with the protected space; the concept of abstract protected elements is introduced and their relationship with the measure of the protected space in the general case of dimensions longer than three is determined. On the basis of the analysis, the requirements for the structure and placement of the security radar are formulated, which are interdependent on the dimension of the protected area, the topology of the security perimeter, the composition, structure, tactical and technical features of the security radar and tactical, technical, operational, environmental and economic quality indicators. The features of the formation of the structure and placement of single- and multi-position security radars under various initial conditions and requirements, as well as approaches to calculating the coordinates of the placement of their elements on the ground are shown.

Adaptive Beamsteering Cognitive Radar With Integrated Search-and-Track of Swarm Targets

Adaptive beamsteering cognitive radar (AB-CRr) systems seek to improve detection and tracking performance by formulating a beam placement strategy adapted to their environment. AB-CRr builds a probabilistic model of the target environment that enables it to more efficiently employ its limited resources to locate and track targets. In this work, we investigate methods for adapting the AB-CRr framework to detect and track large target swarms. This is achieved by integrating the properties of correlated-motion swarms into both the radar tracking model and AB-CRr’s underlying dynamic probability model. As a result, a list of newly CRr-integrated contributions are enumerated: a) improved uncertainty function design, b) incorporates Mahalanobis nearest neighbors multi-target association methodology into AB-CRr, c) introduces a novel Kalman-based consolidated swarm tracking methodology with a common velocity state vector that frames targets as a correlated collection of swarm members, d) introduces an improved uncertainty growth model for updating environment probability map, e) introduces a method for incorporating estimated swarm structure and behavior into the uncertainty update model referred to as “track hinting”, and f) introduces new metrics for swarm search/detection and tracking called swarm centroid track error and swarm tracking dwell ratio. The results demonstrate that AB-CRr is capable of adapting its beamsteering strategy to efficiently perform resource balancing between target search and swarm tracking applications, while taking advantage of group structure and intra-swarm target correlation to resist large swarms overloading available resources.

Differentiated Instruction and Improving Student Learning: A Qualitative Study

Administration and ministers of elementary schools located in the target district in the Caribbean reported that some elementary teachers were inconsistently implementing differentiated instruction (DI) in their practice. Based on the identified problem, it was unclear which specific strategies of DI were causing teachers to experience barriers or challenges during the process of implementation. The purpose of this basic qualitative study was to explore teacher perceptions in one district about their implementation of the conceptual framework, Weimer’s learner-centered teaching theory DI model, in their classroom instruction. Data from schools in one elementary school district in the Beach School District were collected through virtual interviews with 15 teacher participants who had 5 to 10 years of teaching experience for Grades 5 to 6. Data were analyzed with open coding using the RADaR model of analysis. Results indicated that, when teachers use limited and repetitive DI strategies, their use of the DI model in their practice is inconsistent. In addition, teachers indicated they would benefit from some additional training on alternative DI strategies as well as how to effectively differentiate their instruction consistently. The results of this research may contribute to positive social change by providing classroom teachers with additional resources and training to improve the implementation of DI in the classroom and enhance the learning experiences of students.