Multiplatform GMTI Radar Adaptive Clutter Suppression
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Solution Overview
Problem
GMTI radar systems face challenges in detecting slow-moving targets due to their limited minimum detectable velocity (MDV), which is constrained by the physical size of the radar antenna aperture, and require precise tracking of antenna phase centers, making it difficult to achieve adequate signal-to-noise ratio (SNR) and accurate clutter cancellation.
Innovation Solution
A multiplatform GMTI radar system with adaptive clutter suppression is implemented, combining signals from multiple mobile platforms to create a large effective electrical aperture, allowing for clutter cancellation and monopulse angle estimation without the need for precise tracking of antenna phase centers, ensuring adequate SNR for detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the size of the radar antenna aperture is increased to reduce minimum detectable velocity, then the MDV is reduced, but the physical constraints of the aircraft platform limit the antenna size
Solution Approach 1:
The radar system is divided into multiple independent radar units distributed across different platforms (airborne, spaceborne, ground-based). Each platform carries its own radar antenna, and the signals from these segmented radars are combined through adaptive processing to achieve the effect of a large aperture system without requiring a single large physical antenna.
Solution Approach 2:
The system transitions from a single-platform two-dimensional antenna aperture to a multiplatform three-dimensional distributed aperture. By utilizing spatial separation across multiple platforms in different dimensions (altitude, latitude, longitude), the effective electrical aperture is dramatically increased without being constrained by any single platform's physical size.
2Measurement precision
If multiple platforms are used to increase effective aperture, then the MDV is reduced, but precise tracking of antenna phase centers is required which increases system complexity
Solution Approach 1:
The system uses the natural motion characteristics of the platforms and the radar signals themselves to determine relative positions and phase centers. The adaptive signal processing automatically compensates for platform movements and maintains coherent combining without requiring external precision tracking systems, making the system self-sufficient in managing its own geometric relationships.
Solution Approach 2:
The system dynamically adjusts processing parameters including phase shifts, time delays, and weightings based on the real-time relative positions and velocities of the platforms. By changing these parameters adaptively rather than maintaining fixed precise tracking, the system achieves coherent signal combining while reducing the complexity of continuous precision navigation requirements.
3Reliability
If adaptive clutter suppression is applied to improve target detection, then the signal-to-noise ratio is improved, but the processing complexity increases
Solution Approach 1:
The signal processing is segmented into distinct functional modules: coherent integration of multiplatform signals, adaptive clutter suppression processing, and target detection. Each module handles a specific aspect of the processing chain, allowing for optimized and independent implementation of each function while maintaining overall system effectiveness.
Solution Approach 2:
The adaptive clutter suppression employs feedback mechanisms where the processed signals from multiple platforms are combined, and the combination weights and phase adjustments are continuously optimized based on the detected clutter and target characteristics. This feedback-driven adaptation improves SNR by dynamically adjusting to the environmental conditions while the modular architecture manages the processing complexity.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach significantly reduces the minimum detectable velocity and maintains accurate angle estimation while providing improved signal-to-noise ratio, enabling the detection of slow-moving targets without the need for precise navigation of the platforms.
Implementation Method 1
A radar system transmits radio frequency (RF) signals in a predetermined direction (i.e., a bearing) with the intention of contacting or illuminating moving or stationary objects, depending on the radar type, ('targets'). When the transmitted radar signal illuminates a target, a return signal is reflected back toward the radar receiver.
Implementation Method 2
GMTI radars use the Doppler Effect to distinguish moving targets from stationary ones. (When a target approaches the radar receiver, its velocity component parallel to the line of sight of the radar imparts a positive frequency shift if moving towards the radar, and a negative frequency shift if moving away from the radar. This frequency shift is referred to as Doppler and the relevant velocity component is the Doppler velocity.)
Data Source
AI summary
The present invention is directed to a ground moving target (GMTI) radar that can detect targets, including dismounts, with very small minimum detectable velocities by combining signals from antennas on different spatially separated platforms in a main beam clutter-suppressing spatially adaptive process without requiring that the relative positions of the antenna phase centers be accurately tracked. The clutter nulling is in addition to that provided by the Doppler filters. The spatial displacement provides a narrow mainbeam clutter null reducing undesired target suppression. The clutter-suppressing spatially adaptive structure is used in both the sum and delta channels of the monopulse processor so that the beam distortion caused by the spatial nulling is compensated for, and the monopulse look-up process is preserved to maintain angle accuracy. Noncoherent integration is employed to recover signal to noise loss resulting from the uncertain relative locations of the platforms.