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 the limitations of their 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 implement mobile multiplatform systems effectively.
Innovation Solution
A multiplatform GMTI radar system is configured with a distributed antenna array across multiple mobile platforms, using space-time adaptive processing (STAP) to combine radar return signals and cancel clutter without the need for accurate tracking of antenna phase centers, effectively increasing the electrical size of the antenna aperture and reducing MDV.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the antenna aperture size is increased to reduce minimum detectable velocity, then the radar's ability to detect slow-moving targets is improved, but the physical size constraints of the aircraft platform prevent further increases in aperture size
Solution Approach 1:
The radar system is divided into multiple independent receiver platforms, each with its own antenna and receiver. These segmented receivers are distributed across multiple aircraft or platforms, allowing the system to achieve a large effective aperture without requiring a single large physical antenna structure on one platform.
Solution Approach 2:
The system transitions from a single-platform two-dimensional antenna arrangement to a multiplatform three-dimensional distributed array. By utilizing the spatial distribution across multiple platforms in three-dimensional space, the system achieves a large effective aperture without being constrained by the physical dimensions of any single platform.
2Reliability
If conventional GMTI radar processing is used to filter clutter, then stationary background clutter is suppressed, but slow-moving targets below the minimum detectable velocity are masked by remaining clutter and cannot be detected
Solution Approach 1:
The system uses adaptive processing that incorporates feedback from the actual received signals to dynamically adjust the filtering characteristics. The space-time adaptive processor continuously adapts to the clutter environment by analyzing the received signals and adjusting the weight vectors to optimally suppress clutter while preserving target signals, even those with very low velocities.
Solution Approach 2:
The system changes the processing parameters by incorporating both spatial and temporal dimensions in the adaptive filtering. Instead of using only Doppler frequency filtering, the system utilizes space-time adaptive processing that adjusts both the spatial beamforming weights and the temporal Doppler filters dynamically based on the observed clutter and target characteristics, enabling detection of targets with velocities below the conventional minimum detectable velocity.
3Measurement precision
If multiple mobile platforms are used to increase aperture size, then the electrical size of the antenna array is increased, but precise tracking of antenna phase centers becomes difficult and computationally complex
Solution Approach 1:
Each receiver platform independently processes its own received signals and performs self-calibration using the known transmitted signal characteristics. The platforms autonomously determine their own position and orientation information without requiring complex inter-platform coordination or external tracking infrastructure, reducing the overall system complexity.
Solution Approach 2:
The system replaces complex mechanical tracking and position measurement systems with computational methods. Instead of using precise mechanical trackers to monitor antenna phase centers, the system uses signal processing algorithms that compute the effective aperture and perform adaptive beamforming based on the received signal characteristics and known platform geometry, significantly reducing mechanical 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 allows for the detection of ground moving targets with very small minimum detectable velocities while maintaining target signal strength, reducing the need for precise navigation and increasing the radar's ability to distinguish targets from clutter, thereby enhancing situational awareness without the constraints of physical antenna size or tracking accuracy.
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 objects ('contacts'). When the transmitted radar signal illuminates a contact, a return signal is reflected back toward the radar receiver.
Implementation Method 2
GMTI radars use the Doppler Effect to distinguish moving contacts from stationary ones. (When a contact 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 main beam 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.