FDA Jamming Against Airborne Phased-MIMO Radar-Part II: Jamming STAP Performance Analysis
Summary
This paper is Part II of a two-part series on frequency diverse array (FDA) jamming against airborne phased-MIMO radar. Notes on part II were provided in a previous post. The key points are:
1. It focuses on FDA scattered wave (FDA-SW) jamming against space-time adaptive processing (STAP) in phased-MIMO radar.
2. The authors derive equations for the spatial frequency and Doppler frequency of FDA-SW jamming based on the trajectory of ground scatterers.
3. They analyze how the FDA jamming frequency offset affects the clutter rank and STAP performance for different phased-MIMO radar configurations:
- For phased-array radar, FDA jamming doesn't affect clutter rank
- For FDA-MIMO radar, it increases clutter rank
4. The paper shows how adjusting the FDA jamming frequency offset can shift the Doppler-dimensional position of the improvement factor (IF) notch, potentially protecting targets.
5. Requirements for the jamming frequency offset are discussed for different applications across both parts of the series.
6. Simulations verify the theoretical analysis, demonstrating FDA-SW jamming can:
- Increase clutter rank for FDA-MIMO radar
- Shift the spatial-Doppler spectrum
- Affect the IF notch position
7. The authors discuss limitations of their work and suggest future research directions, including expanding FDA jamming categories, analyzing effects on parameter estimation and tracking, and developing countermeasures.
In summary, this paper provides a theoretical and simulation-based analysis of how FDA-SW jamming can degrade STAP performance in phased-MIMO radar by manipulating clutter characteristics and IF notches.
1. It focuses on FDA scattered wave (FDA-SW) jamming against space-time adaptive processing (STAP) in phased-MIMO radar.
2. The authors derive equations for the spatial frequency and Doppler frequency of FDA-SW jamming based on the trajectory of ground scatterers.
3. They analyze how the FDA jamming frequency offset affects the clutter rank and STAP performance for different phased-MIMO radar configurations:
- For phased-array radar, FDA jamming doesn't affect clutter rank
- For FDA-MIMO radar, it increases clutter rank
4. The paper shows how adjusting the FDA jamming frequency offset can shift the Doppler-dimensional position of the improvement factor (IF) notch, potentially protecting targets.
5. Requirements for the jamming frequency offset are discussed for different applications across both parts of the series.
6. Simulations verify the theoretical analysis, demonstrating FDA-SW jamming can:
- Increase clutter rank for FDA-MIMO radar
- Shift the spatial-Doppler spectrum
- Affect the IF notch position
7. The authors discuss limitations of their work and suggest future research directions, including expanding FDA jamming categories, analyzing effects on parameter estimation and tracking, and developing countermeasures.
In summary, this paper provides a theoretical and simulation-based analysis of how FDA-SW jamming can degrade STAP performance in phased-MIMO radar by manipulating clutter characteristics and IF notches.
Figures and Tables
The paper includes several figures and tables intended to illustrate key concepts and simulation results. Here's a list with a brief discussion of each:
Figures:
1. Figure 1: The radar detection scenario of FDA-SW jamming and clutter
- Shows the geometric setup of the radar, jammer, and ground scatterers
- Illustrates the difference between clutter and jamming trajectories
2. Figure 2: The receiver structure for phased-MIMO-STAP
- Depicts the signal processing chain in the radar receiver
- Helps understand how the jamming affects different stages of processing
3. Figure 3: Effect of Δf' for FDA jamming on the clutter rank of PA radar
- Demonstrates that FDA jamming doesn't affect clutter rank for phased-array radar
- Shows increased clutter eigenvalues due to jamming
4. Figure 4: Effect of Δf' for SF jamming on the clutter rank of FDA-MIMO radar
- Illustrates how SF jamming increases clutter rank for FDA-MIMO radar
- Shows the impact of different jamming frequency offsets
5. Figure 5: Effect of Δf' for AF jamming on the clutter rank of FDA-MIMO radar
- Similar to Figure 4, but for AF jamming
- Allows comparison between SF and AF jamming effects
6. Figure 6: The spatial-Doppler spectrums of four subarrays of phased-MIMO radar under different jamming frequency offsets
- Eight subplots (a-h) showing how jamming shifts the spatial-Doppler spectrum
- Demonstrates how jamming can overlap with or separate from the target spectrum
7. Figure 7: Effect of the small Δf' for SF jamming
- Shows Improvement Factor (IF) changes with small jamming frequency offsets
- Illustrates widening of the main IF notch and emergence of secondary notches
8. Figure 8: Effect of the big Δf' for SF jamming
- Demonstrates IF changes with larger jamming frequency offsets
- Shows how the secondary notch shifts and becomes shallower
9. Figure 9: Effect of the small Δf' for AF jamming
- Similar to Figure 7, but for AF jamming
- Allows comparison of SF and AF jamming effects on IF
10. Figure 10: Effect of the big Δf' for AF jamming
- Similar to Figure 8, but for AF jamming
- Further illustrates differences between SF and AF jamming at higher frequency offsets
11. Figure 11: The trajectory of the ground scatterers for FDA scattered wave jamming
- Located in an appendix, this figure helps explain the mathematical derivation of the scatterer trajectory
Tables:
1. Table I: Simulation Parameters
- Lists all the key parameters used in the simulations
- Provides a reference for understanding the simulation setup and potentially reproducing results
2. Table II: Comparison of the FDA jamming and existing Doppler jamming techniques
- Compares FDA jamming with other jamming techniques
- Highlights the unique features, advantages, and potential drawbacks of FDA jamming
These figures and tables collectively illustrate the theoretical concepts, simulation setup, and key results of the study, providing visual and tabular support for the paper's main arguments about the effectiveness of FDA jamming against phased-MIMO radar STAP.
Figures:
1. Figure 1: The radar detection scenario of FDA-SW jamming and clutter
- Shows the geometric setup of the radar, jammer, and ground scatterers
- Illustrates the difference between clutter and jamming trajectories
2. Figure 2: The receiver structure for phased-MIMO-STAP
- Depicts the signal processing chain in the radar receiver
- Helps understand how the jamming affects different stages of processing
3. Figure 3: Effect of Δf' for FDA jamming on the clutter rank of PA radar
- Demonstrates that FDA jamming doesn't affect clutter rank for phased-array radar
- Shows increased clutter eigenvalues due to jamming
4. Figure 4: Effect of Δf' for SF jamming on the clutter rank of FDA-MIMO radar
- Illustrates how SF jamming increases clutter rank for FDA-MIMO radar
- Shows the impact of different jamming frequency offsets
5. Figure 5: Effect of Δf' for AF jamming on the clutter rank of FDA-MIMO radar
- Similar to Figure 4, but for AF jamming
- Allows comparison between SF and AF jamming effects
6. Figure 6: The spatial-Doppler spectrums of four subarrays of phased-MIMO radar under different jamming frequency offsets
- Eight subplots (a-h) showing how jamming shifts the spatial-Doppler spectrum
- Demonstrates how jamming can overlap with or separate from the target spectrum
7. Figure 7: Effect of the small Δf' for SF jamming
- Shows Improvement Factor (IF) changes with small jamming frequency offsets
- Illustrates widening of the main IF notch and emergence of secondary notches
8. Figure 8: Effect of the big Δf' for SF jamming
- Demonstrates IF changes with larger jamming frequency offsets
- Shows how the secondary notch shifts and becomes shallower
9. Figure 9: Effect of the small Δf' for AF jamming
- Similar to Figure 7, but for AF jamming
- Allows comparison of SF and AF jamming effects on IF
10. Figure 10: Effect of the big Δf' for AF jamming
- Similar to Figure 8, but for AF jamming
- Further illustrates differences between SF and AF jamming at higher frequency offsets
11. Figure 11: The trajectory of the ground scatterers for FDA scattered wave jamming
- Located in an appendix, this figure helps explain the mathematical derivation of the scatterer trajectory
Tables:
1. Table I: Simulation Parameters
- Lists all the key parameters used in the simulations
- Provides a reference for understanding the simulation setup and potentially reproducing results
2. Table II: Comparison of the FDA jamming and existing Doppler jamming techniques
- Compares FDA jamming with other jamming techniques
- Highlights the unique features, advantages, and potential drawbacks of FDA jamming
These figures and tables collectively illustrate the theoretical concepts, simulation setup, and key results of the study, providing visual and tabular support for the paper's main arguments about the effectiveness of FDA jamming against phased-MIMO radar STAP.
Simulations
The paper presents several simulations to verify the theoretical analysis and demonstrate the effectiveness of FDA-SW jamming against phased-MIMO radar STAP. Here's a breakdown of the simulations and key results:
1. Simulation Parameters:
- Carrier frequency: 10 GHz
- Platform height: 2000 m
- Pulse repetition interval: 100 μs
- Platform velocity: 75 m/s
- Number of transmit/receive antennas: 8 each
- Number of pulses: 8
- Target range: 6 km
- INR: 30 dB, SNR: 10 dB
2. Clutter Rank Analysis:
- For phased-array radar: FDA jamming doesn't affect clutter rank but increases clutter eigenvalues.
- For FDA-MIMO radar: FDA jamming increases clutter rank from about 19 to a range of 19-37, confirming theoretical predictions.
3. Spatial-Doppler Spectrum:
- Simulations show how different jamming frequency offsets affect the spatial-Doppler spectrum.
- With no jamming (Δf' = 0 kHz), clutter and target spectra are separate.
- As jamming frequency offset increases, the jamming spectrum shifts and can overlap with the target spectrum.
- This demonstrates how FDA jamming can protect a target by making it indistinguishable from jamming in the spatial-Doppler domain.
4. Improvement Factor (IF) Analysis:
- Simulations show IF for phased-MIMO-STAP under different jamming conditions.
- For small frequency offsets:
- FDA jamming widens the IF notch, increasing the minimum detectable velocity.
- As offset increases, a second notch appears and shifts.
- For large frequency offsets:
- The second notch continues to shift but becomes shallower due to energy loss after matched filtering.
- The main notch (at Doppler frequency 0) is less affected by larger offsets.
5. Comparison of SF and AF Jammers:
- AF jammers generally require slightly larger frequency offsets to achieve effects similar to SF jammers.
- Results are consistent for both jammer types, validating the theoretical analysis.
6. Verification of Theoretical Predictions:
- The simulations confirm the derived equations for Doppler shift and clutter rank changes.
- They also validate the proposed frequency offset requirements for different jamming scenarios.
Overall, the simulation results demonstrate that FDA-SW jamming can effectively degrade STAP performance by increasing clutter rank, shifting the spatial-Doppler spectrum, and manipulating IF notches. The results align well with the theoretical analysis, supporting the paper's conclusions about the potential effectiveness of FDA jamming against phased-MIMO radar systems.
1. Simulation Parameters:
- Carrier frequency: 10 GHz
- Platform height: 2000 m
- Pulse repetition interval: 100 μs
- Platform velocity: 75 m/s
- Number of transmit/receive antennas: 8 each
- Number of pulses: 8
- Target range: 6 km
- INR: 30 dB, SNR: 10 dB
2. Clutter Rank Analysis:
- For phased-array radar: FDA jamming doesn't affect clutter rank but increases clutter eigenvalues.
- For FDA-MIMO radar: FDA jamming increases clutter rank from about 19 to a range of 19-37, confirming theoretical predictions.
3. Spatial-Doppler Spectrum:
- Simulations show how different jamming frequency offsets affect the spatial-Doppler spectrum.
- With no jamming (Δf' = 0 kHz), clutter and target spectra are separate.
- As jamming frequency offset increases, the jamming spectrum shifts and can overlap with the target spectrum.
- This demonstrates how FDA jamming can protect a target by making it indistinguishable from jamming in the spatial-Doppler domain.
4. Improvement Factor (IF) Analysis:
- Simulations show IF for phased-MIMO-STAP under different jamming conditions.
- For small frequency offsets:
- FDA jamming widens the IF notch, increasing the minimum detectable velocity.
- As offset increases, a second notch appears and shifts.
- For large frequency offsets:
- The second notch continues to shift but becomes shallower due to energy loss after matched filtering.
- The main notch (at Doppler frequency 0) is less affected by larger offsets.
5. Comparison of SF and AF Jammers:
- AF jammers generally require slightly larger frequency offsets to achieve effects similar to SF jammers.
- Results are consistent for both jammer types, validating the theoretical analysis.
6. Verification of Theoretical Predictions:
- The simulations confirm the derived equations for Doppler shift and clutter rank changes.
- They also validate the proposed frequency offset requirements for different jamming scenarios.
Overall, the simulation results demonstrate that FDA-SW jamming can effectively degrade STAP performance by increasing clutter rank, shifting the spatial-Doppler spectrum, and manipulating IF notches. The results align well with the theoretical analysis, supporting the paper's conclusions about the potential effectiveness of FDA jamming against phased-MIMO radar systems.
Performance and Tactical Implications
The simulations in this paper demonstrate several significant performance impacts of FDA-SW jamming against airborne MIMO STAP radars, with important tactical electronic warfare (EW) implications:
1. Clutter Rank Manipulation:
- For FDA-MIMO radar, FDA jamming increased the clutter rank from about 19 to a range of 19-37.
- Tactical implication: This complicates clutter suppression, potentially masking targets and reducing detection range.
2. Spatial-Doppler Spectrum Shifting:
- By adjusting the jamming frequency offset, the FDA-SW jamming can shift its spectrum to overlap with potential target locations.
- Tactical implication: This can protect specific targets by making them indistinguishable from jamming in the spatial-Doppler domain.
3. Improvement Factor (IF) Notch Manipulation:
- FDA jamming widened the main IF notch and created additional notches.
- The position of these notches can be controlled by adjusting the jamming frequency offset.
- Tactical implication: This increases the radar's minimum detectable velocity and can create "blind spots" in velocity detection, protecting moving targets.
4. Flexible Jamming Effects:
- Different effects were achieved by adjusting the jamming frequency offset.
- Tactical implication: A single FDA jammer could potentially adapt its strategy based on the tactical situation, target characteristics, or observed radar behavior.
5. Effectiveness Against Advanced Radar:
- The jamming was effective against both phased-array and FDA-MIMO radar configurations.
- Tactical implication: FDA jamming presents a threat even to cutting-edge radar systems, potentially negating some advantages of FDA-MIMO technology.
6. Range-Dependent Effects:
- The jamming's impact varies with target range due to the nature of FDA.
- Tactical implication: This could allow for selective protection of targets at specific ranges or complicating radar operation across its entire range.
7. Coherent Jamming:
- FDA-SW jamming maintains coherence with the radar signal.
- Tactical implication: This makes it more difficult for the radar to distinguish jamming from valid returns using traditional techniques.
8. Increased False Alarms:
- The jamming can generate false targets and increase clutter.
- Tactical implication: This could overwhelm radar operators or automated tracking systems, reducing overall situational awareness.
Overall, these simulations demonstrate that FDA-SW jamming could significantly degrade the performance of airborne MIMO STAP radars. Tactically, this type of jamming offers flexible options for protecting aircraft, vehicles, or other assets from detection and tracking. It could be particularly effective in scenarios where traditional noise jamming might be less successful due to advanced STAP techniques.
The ability to manipulate clutter characteristics and create controlled blind spots in radar coverage provides sophisticated options for electronic attack. However, the complexity and potential cost of FDA jammers, along with their requirement for accurate knowledge of radar parameters, might limit their deployment to high-value protection scenarios or advanced electronic warfare platforms.
1. Clutter Rank Manipulation:
- For FDA-MIMO radar, FDA jamming increased the clutter rank from about 19 to a range of 19-37.
- Tactical implication: This complicates clutter suppression, potentially masking targets and reducing detection range.
2. Spatial-Doppler Spectrum Shifting:
- By adjusting the jamming frequency offset, the FDA-SW jamming can shift its spectrum to overlap with potential target locations.
- Tactical implication: This can protect specific targets by making them indistinguishable from jamming in the spatial-Doppler domain.
3. Improvement Factor (IF) Notch Manipulation:
- FDA jamming widened the main IF notch and created additional notches.
- The position of these notches can be controlled by adjusting the jamming frequency offset.
- Tactical implication: This increases the radar's minimum detectable velocity and can create "blind spots" in velocity detection, protecting moving targets.
4. Flexible Jamming Effects:
- Different effects were achieved by adjusting the jamming frequency offset.
- Tactical implication: A single FDA jammer could potentially adapt its strategy based on the tactical situation, target characteristics, or observed radar behavior.
5. Effectiveness Against Advanced Radar:
- The jamming was effective against both phased-array and FDA-MIMO radar configurations.
- Tactical implication: FDA jamming presents a threat even to cutting-edge radar systems, potentially negating some advantages of FDA-MIMO technology.
6. Range-Dependent Effects:
- The jamming's impact varies with target range due to the nature of FDA.
- Tactical implication: This could allow for selective protection of targets at specific ranges or complicating radar operation across its entire range.
7. Coherent Jamming:
- FDA-SW jamming maintains coherence with the radar signal.
- Tactical implication: This makes it more difficult for the radar to distinguish jamming from valid returns using traditional techniques.
8. Increased False Alarms:
- The jamming can generate false targets and increase clutter.
- Tactical implication: This could overwhelm radar operators or automated tracking systems, reducing overall situational awareness.
Overall, these simulations demonstrate that FDA-SW jamming could significantly degrade the performance of airborne MIMO STAP radars. Tactically, this type of jamming offers flexible options for protecting aircraft, vehicles, or other assets from detection and tracking. It could be particularly effective in scenarios where traditional noise jamming might be less successful due to advanced STAP techniques.
The ability to manipulate clutter characteristics and create controlled blind spots in radar coverage provides sophisticated options for electronic attack. However, the complexity and potential cost of FDA jammers, along with their requirement for accurate knowledge of radar parameters, might limit their deployment to high-value protection scenarios or advanced electronic warfare platforms.
Limitations and Future Directions
While the authors provide a comprehensive analysis and suggest several future research directions, there are additional limitations and potential areas for future work that could be considered:
2. Single-Target Focus: The analysis primarily considers a single target. Multi-target scenarios might reveal additional complexities or limitations of the FDA jamming approach.
3. Limited Radar Configurations: While the paper considers phased-array and FDA-MIMO radars, other advanced configurations (e.g., cognitive radar, multi-static systems) are not addressed.
4. Static Analysis: The simulations don't consider dynamic scenarios where the jammer or targets are maneuvering relative to the radar.
5. Simplified Propagation Model: The paper doesn't account for complex propagation effects like multipath, atmospheric ducting, or terrain interactions.
6. Power Requirements: The energy efficiency and practical power requirements for FDA jammers are not thoroughly addressed.
2. Multi-Platform Coordinated Jamming: Investigate how multiple FDA jammers could cooperate to create more complex and effective jamming scenarios.
3. Counter-Counter Measures: Explore potential radar adaptations or signal processing techniques that could mitigate the effects of FDA jamming.
4. Information Theoretic Analysis: Apply information theory to quantify the reduction in radar channel capacity due to FDA jamming.
5. Hardware Implementation Challenges: Investigate the practical challenges of building FDA jammers, including phase synchronization, thermal management, and size/weight constraints.
6. Integration with Cyber Attacks: Explore how FDA jamming could be combined with cyber attacks on radar systems for enhanced effectiveness.
7. FDA Jamming in Cluttered Environments: Analyze the effectiveness of FDA jamming in complex urban or littoral environments with significant clutter.
8. Quantum Sensing Interactions: As quantum sensing technologies emerge, study how FDA jamming might interact with or be adapted for quantum radar systems.
9. Machine Learning for Jammer Optimization: Develop ML algorithms to optimize FDA jammer parameters in complex, multi-target scenarios.
10. Bi-static and Multi-static Effects: Extend the analysis to consider how FDA jamming affects bi-static and multi-static radar configurations.
11. Electronic Protection Measures: Research new electronic protection measures specifically designed to counter FDA jamming techniques.
12. Jamming Effects on SAR/ISAR Imaging: Analyze how FDA jamming impacts synthetic aperture radar (SAR) and inverse SAR imaging capabilities.
These additional research directions could further advance the understanding of FDA jamming and its implications for modern electronic warfare.
Limitations:
1. Idealized Scenario: The simulations assume perfect knowledge of radar parameters and target characteristics. Real-world scenarios would involve uncertainties and estimation errors.2. Single-Target Focus: The analysis primarily considers a single target. Multi-target scenarios might reveal additional complexities or limitations of the FDA jamming approach.
3. Limited Radar Configurations: While the paper considers phased-array and FDA-MIMO radars, other advanced configurations (e.g., cognitive radar, multi-static systems) are not addressed.
4. Static Analysis: The simulations don't consider dynamic scenarios where the jammer or targets are maneuvering relative to the radar.
5. Simplified Propagation Model: The paper doesn't account for complex propagation effects like multipath, atmospheric ducting, or terrain interactions.
6. Power Requirements: The energy efficiency and practical power requirements for FDA jammers are not thoroughly addressed.
Additional Future Research Directions:
1. Cognitive FDA Jamming: Develop adaptive FDA jamming strategies that can learn and respond to changing radar behaviors in real-time.2. Multi-Platform Coordinated Jamming: Investigate how multiple FDA jammers could cooperate to create more complex and effective jamming scenarios.
3. Counter-Counter Measures: Explore potential radar adaptations or signal processing techniques that could mitigate the effects of FDA jamming.
4. Information Theoretic Analysis: Apply information theory to quantify the reduction in radar channel capacity due to FDA jamming.
5. Hardware Implementation Challenges: Investigate the practical challenges of building FDA jammers, including phase synchronization, thermal management, and size/weight constraints.
6. Integration with Cyber Attacks: Explore how FDA jamming could be combined with cyber attacks on radar systems for enhanced effectiveness.
7. FDA Jamming in Cluttered Environments: Analyze the effectiveness of FDA jamming in complex urban or littoral environments with significant clutter.
8. Quantum Sensing Interactions: As quantum sensing technologies emerge, study how FDA jamming might interact with or be adapted for quantum radar systems.
9. Machine Learning for Jammer Optimization: Develop ML algorithms to optimize FDA jammer parameters in complex, multi-target scenarios.
10. Bi-static and Multi-static Effects: Extend the analysis to consider how FDA jamming affects bi-static and multi-static radar configurations.
11. Electronic Protection Measures: Research new electronic protection measures specifically designed to counter FDA jamming techniques.
12. Jamming Effects on SAR/ISAR Imaging: Analyze how FDA jamming impacts synthetic aperture radar (SAR) and inverse SAR imaging capabilities.
These additional research directions could further advance the understanding of FDA jamming and its implications for modern electronic warfare.
Authors
See prior post on part 1. The author list and institutional affiliations are consistent across both papers:
1. Yan Sun University of Electronic Science and Technology of China, Chengdu, China
2. Wen-qin Wang (Corresponding author, Senior Member, IEEE) University of Electronic Science and Technology of China, Chengdu, China
3. Zhou He Southwest Jiaotong University, Chengdu, China
4. Shunsheng Zhang University of Electronic Science and Technology of China, Chengdu, China
Prior Related Work:
While the papers don't directly list the authors' previous works, we can infer from the content and depth of analysis that they have significant expertise in:
1. Phased-MIMO radar systems
2. Frequency Diverse Array (FDA) techniques
3. Space-Time Adaptive Processing (STAP)
4. Electronic Countermeasures (ECM) and Counter-Countermeasures (ECCM)
5. Signal processing for radar systems
The two-part series itself represents a substantial body of work on FDA jamming:
- Part I focuses on the effectiveness of FDA jamming through direct wave propagation, analyzing its impact on matched filtering and spatial filtering in phased-MIMO radar.
- Part II extends this to FDA scattered wave (FDA-SW) jamming, examining its effects on STAP performance.
Together, these papers present a comprehensive framework for FDA jamming against airborne phased-MIMO radar, covering both direct and scattered wave propagation scenarios.
The collaboration between the University of Electronic Science and Technology of China and Southwest Jiaotong University suggests a strong research partnership in this field.
Wen-qin Wang's status as a Senior Member of IEEE and role as corresponding author indicate a leadership position in this research area and likely a significant publication history in related topics.
Electrical Engineering and Systems Science > Signal Processing
[Submitted on 6 Aug 2024]
The first part of this series introduced the effectiveness of frequency diverse array (FDA) jamming through direct wave propagation in countering airborne phased multiple-input multiple-output (Phased-MIMO) radar.
This part focuses on the effectiveness of FDA scattered wave (FDA-SW) jamming on the space-time adaptive processing (STAP) for airborne phased-MIMO radar. Distinguished from the clutter signals, the ground equidistant scatterers of FDA-SW jamming constitute an elliptical ring, whose trajectory equations are mathematically derived to further determine the spatial frequency and Doppler frequency. For the phased-MIMO radar with different transmitting partitions, the effects of jamming frequency offset of FDA-SW on the clutter rank and STAP performance are discussed.
Theoretical analysis provides the variation interval of clutter rank and the relationship between the jamming frequency offset and the improvement factor (IF) notch of phased-MIMO-STAP. Importantly, the requirements of jamming frequency offset for both two-part applications are discussed in this part. Numerical results verify these mathematical findings and validate the effectiveness of the proposed FDA jamming in countering the phased-MIMO radar.
Submission history
From: Yan Sun [view email][v1] Tue, 6 Aug 2024 09:17:27 UTC (5,452 KB)
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