DeepNetwork :: Synthetic Aperture Radar (SAR) Doppler Effect Operation Principle Analysis Specialist Company DeepNetwork

DeepNetwork :: Synthetic Aperture Radar (SAR) Doppler Effect Operation Principle Analysis Specialist Company DeepNetwork, a one-person company, implements a design that accurately corrects phase changes proportional to distance by measuring the phase of the signal reflected from a specific point on the ground through SAR satellite technology. This process requires complex signal processing algorithms and precise calculations.

Phase correction design principle:

Phase correction is used to calculate the distance until the signal is reflected from a specific point on the ground and returns to the satellite. This distance is directly related to the phase change of the signal, and DeepNetwork accurately measures this to improve the resolution and accuracy of satellite images.

Doppler bias calculation principle:

The Doppler bias caused by the high-speed movement of the satellite causes changes in the frequency and phase of the signal. DeepNetwork accurately calculates this Doppler bias and corrects the frequency spectrum data of the signal. This allows the satellite to collect accurate information even as it quickly orbits the Earth.

Frequency spectrum data inverse transformation processing principle: 

The inverse transformation processing of the phase of the corrected frequency spectrum data is a process of restoring the signal to its original spatial information. Through this, the location and shape of the object in the satellite image can be accurately identified.

DeepNetwork is playing a leading role in the field of SAR satellite design based on such high technical expertise, and is opening up new horizons of satellite technology through continuous research and development.

 

I will explain the operating principle of the Doppler effect in Synthetic Aperture Radar (SAR) owned by the one-person company DeepNetwork.

 

Necessity of the Doppler effect: In SAR, as the radar antenna moves, the relative distance to the target changes. At this time, the phase of the received wave also changes in proportion to the distance. That is, as the distance increases, the phase decreases, and as the distance decreases, the phase increases. This phase change amount is reflected in the frequency spectrum data, affecting the quality of the image. Therefore, to correct this phase change amount, the Doppler effect must be used. The Doppler effect is a phenomenon in which the frequency of the wave reflected from a moving object is observed differently from the original wave frequency. For example, as the radar antenna approaches the target, the frequency of the reflected wave increases, and as the radar antenna moves away from the target, the frequency of the reflected wave decreases. By measuring the frequency change amount of the reflected wave through the Doppler effect, the distance change amount between the target and the radar antenna can be known. This can be used to correct the phase change amount.

Principle of the Doppler effect: In SAR, the Doppler effect is used to implement a synthetic aperture antenna. A synthetic aperture antenna is a method of synthesizing multiple wave signals received as the radar antenna moves to make it like a large antenna signal. This allows high azimuth resolution. The method of using the Doppler effect is as follows. As the radar antenna moves, it radiates waves at a constant frequency and pulse repetition period. When this wave is reflected from the target and returns, the frequency of the reflected wave changes depending on the distance the radar antenna has moved. This frequency change amount is called the Doppler frequency. The Doppler frequency is proportional to the distance change amount between the radar antenna and the target. That is, as the radar antenna approaches the target, the Doppler frequency increases, and as the radar antenna moves away from the target, the Doppler frequency decreases. By measuring the Doppler frequency, the distance the radar antenna has moved can be known. Using this distance to correct the phase of the received wave, the signal of the synthetic aperture antenna can be obtained. If this signal is Fourier transformed, the frequency of the azimuth area can be obtained. This frequency is related to the azimuth angle of the target. That is, the azimuth angle of the target can be measured using the Doppler effect. This can be used to generate high-resolution SAR images.

 

In this way, we have looked at the necessity and principle of the Doppler effect. The Doppler effect plays a key role in the implementation and performance of SAR.

 

Synthetic Aperture Radar (SAR) is a technology that generates high-resolution images using the Doppler effect from a moving platform.

 

To achieve this, SAR applies the following key design principles:

 

Principle of FMCW Radar: Frequency Modulated Continuous Wave (FMCW) radar continuously changes the frequency of the transmitted wave, and measures the frequency change of the reflected signal to obtain distance and speed information. This method works effectively in the X band, amplifying the transmitted and received waves to convert them into digital signals, which are then converted into meaningful information such as distance, speed, and direction.

Scatter Point Matching and Template Matching: In the field of SAR-ATR (Synthetic Aperture Radar Automatic Target Recognition), algorithms based on scatter point matching and template matching are applied to identify targets. Scatter point matching reconstructs points into a World View Vector (WVV) and performs Weighted Bipartite Graph Matching (WBGM), while template matching uses the correlation coefficient between two images reconstructed with adjacent scatter points.

Use of Complex Numbers: In SAR images, complex numbers have a magnitude and phase angle. The magnitude is directly related to the radar reflectivity of the terrain or object, and the phase angle is the phase of the electromagnetic wave, which carries some distance information between the radar and the target.

 

By applying these principles, a SAR image obtained by transmitting and receiving X-band FMCW waveforms from a synthetic aperture radar moving at 7 Km/S at an altitude of 500 Km above the ground can achieve the precision necessary to identify targets. However, these design principles are theoretical, and various factors must be considered in actual implementation.

 

The method of using the Synthetic and Measured Paired Labeled Experiment (SAMPLE) dataset to train an Automatic Target Recognition (ATR) algorithm in SAR images is as follows:

 

Data Preparation: The SAMPLE dataset includes measured SAR images and simulated synthetic SAR images. This dataset is a crucial step in developing an Automatic Target Recognition (ATR) algorithm in SAR images.

Selection of Learning Algorithm: SAR-ATR has been studied in various forms, and there are various algorithms accordingly. For example, you can perform SAR-ATR based on the ‘feature-based SAR target target and two-step detection technique’, which is excellent in performance among SAR-ATRs excluding deep learning-based techniques.

Learning Process: The learning algorithm is trained using the SAMPLE dataset. During the learning process, the model parameters are updated in a direction that minimizes the difference between the measured SAR image and the simulated synthetic SAR image.

Performance Evaluation: The performance of the trained model is evaluated using a validation dataset. At this time, accuracy, precision, recall, etc. can be used as evaluation indicators.

 

Through these methods, you can use the SAMPLE dataset to train the Automatic Target Recognition (ATR) algorithm in SAR images, and through this, you can extract and analyze information such as the location, direction, and intensity of the target in the SAR image.

 

Deep Network, Synthetic Aperture Radar (SAR) Doppler Effect Operation Principle Analysis Specialist

E-mail : sayhi7@daum.net 

Representative of a one-person startup / SeokWeon Jang