In this paper, we propose a model for multitask target detection based on convolutional neural network (CNN), which works directly with radar echo data and eliminates the need for time-consuming radar signal processing. The proposed detection method exploits time and frequency information ...
Radar detection of maritime targets plays an important role in marine environment monitoring. For civil maritime detection in the areas of inshore coastal, pulse-compression radar is universally used owing to its low cost. The complex sea clutter in the
This example shows how radar detection performance improves as target elevation increases above the terrain. Simulate and Track Targets with Terrain Occlusions (Sensor Fusion and Tracking Toolbox) This example shows you how to model a surveillance scenario in a mountainous region where terrain can ...
Deep CNN-Based Radar Detection for Real Maritime Target Under Different Sea States and PolarizationsMaritime target detection, because of the difficulties in the extraction and recognition of target and clutter micro-motion characteristics, has always been one of the difficulties in radar target......
Yavuz, F. Radar target detection with CNN. In Proceedings of the 2021 29th European Signal Processing Conference (EUSIPCO), Dublin, Ireland, 23–27 August 2021; pp. 1581–1585. [Google Scholar] Liang, X.; Chen, B.; Chen, W.; Wang, P.; Liu, H. Unsupervised radar target detection und...
Figure 8 is the comparison diagram of CNN target detection probability with and without a BN layer. Figure 8. Target detection probability comparison graph of CNN with and without BN layer. As can be seen from the Figure 8, the detection probability with a BN layer is slightly higher than...
2020-RAMP-CNN: A Novel Neural Network for Enhanced Automotive Radar Object Recognition RA; Paper 2020-RADIO Parameterized Generative Radar Data Augmentation for Small Datasets RA; Paper 2016-Convolutional Neural Network With Data Augmentation for SAR Target Recognition GRSL; SAR; Paper Simulator 2024-Ra...
(CNN), Stacked Auto-Encoders), Dimensionality Reduction Algorithms (e.g., Principal Component Analysis (PCA), Principal Component Regression (PCR), Partial Least Squares Regression (PLSR), Sammon Mapping, Multidimensional Scaling (MDS), Projection Pursuit, Linear Discriminant Analysis (LDA), Mixture ...
Waveform Scheduling Based on Target Detection Model a radar that changes its pulse repetition frequency (PRF) based on the radar detection. AI for Radar Improving Weather Radar Moment Estimation with Convolutional Neural Networks Train and evaluate convolutional neural networks (CNN) to improve weather ...
这个例子展示了如何使用深度学习网络和时频分析,根据行人和骑自行车的人的微多普勒特征进行分类。放置在雷达前的物体的不同部分的运动产生可用于识别物体的微多普勒特征。本例使用卷积神经网络(CNN)根据特征识别行人和骑自行车的人。这个例子使用模拟数据训练深度学习网络,然后检查网络如何对两种重叠签名进行分类。