MIMO Radar Phase Code Scheduling With Two-Step Optimization
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Solution Overview
Problem
Existing MIMO radar systems face computational complexity and suboptimal performance when designing orthogonal phase codes due to exponential increases in computational difficulty, particularly when implementing phase code optimization across multiple transmission channels.
Innovation Solution
A two-step optimization process is employed, where the first step optimizes each phase code as it is added to a stack, avoiding exponential complexity, and the second step compares and constructs a new set of phase codes to minimize the cost function, considering mutual interference and convergence criteria.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If phase code optimization is performed across multiple transmission channels using conventional methods, then orthogonality and performance are improved, but computational complexity increases exponentially
Solution Approach 1:
The patent segments the phase code optimization process into two distinct steps: Step 1 optimizes each phase code individually as it is added to the stack, while Step 2 performs joint optimization of the complete set of phase codes. This segmentation transforms an exponentially complex single-step optimization into two manageable steps with reduced computational burden at each stage, while still achieving the desired orthogonality and performance.
2Measurement precision
If more transmission channels are added to improve radar performance and resolution, then angular resolution and target parameter identifiability are enhanced, but the difficulty of detecting and measuring increases
Solution Approach 1:
By dividing the optimization process into two steps, the patent makes it feasible to handle a larger number of transmission channels. Step 1 processes each channel's phase code individually, and Step 2 refines the complete set, thereby reducing the overall computational difficulty and making it practical to implement systems with more channels for improved angular resolution and target parameter identifiability.
Solution Approach 2:
Step 1 of the optimization process performs preliminary optimization of each phase code before it is added to the stack, establishing a good initial configuration. This preliminary action simplifies the subsequent Step 2 optimization, making the overall process more manageable even as the number of transmission channels increases to enhance measurement precision.
3Reliability
If random offset is applied to LFM signal for MIMO radar operation, then orthogonality is achieved, but physical systems become incapable or suboptimal
Solution Approach 1:
The patent changes the approach from applying random offsets to LFM signals (which are difficult to implement physically) to using optimized phase codes with binary phase shifts. This parameter change maintains the orthogonality requirement while making the system implementable with conventional radar hardware, improving ease of manufacture and physical system implementation.
Data Source
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AI summary
A two-step optimization method for scheduling transmissions in an MIMO (multi-input multi-output) includes determining a first phase code for each transmission according to a first equation, placing each first phase code in a set of first phase codes, and determining a cost function of the set of first phase codes, determining a second phase code for each transmission according to a second equation, determining an updated cost function corresponding to replacing each of the first phase codes with a corresponding one of the second phase codes, and determining which set of phase codes has a smaller cost function.