Phase-Coded Radar Signal Search with Quantum Genetic Algorithms
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Solution Overview
Problem
Conventional genetic algorithms for determining phase-coded radar signals face inefficiencies due to limited population sizes leading to local optima and slow convergence, especially for binary-phase-coded radar signals, which complicates the search process and reduces reliability and efficiency.
Innovation Solution
A quantum genetic algorithm is employed, utilizing P*G*C qubits, quantum rotating gates, and a quantum catastrophe strategy to enhance diversity and parallel computing, allowing for faster convergence and improved search efficiency by enriching the search space and avoiding local optima.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the population size is increased to improve search quality and avoid local optima, then the reliability of results is improved, but the computation time increases proportionally and convergence speed decreases
Solution Approach 1:
The patent replaces the classical genetic algorithm's mechanical evolution process with a quantum genetic algorithm that utilizes quantum parallel computing. The quantum rotating gate updates all chromosomes simultaneously through quantum parallelism, substituting the sequential classical evolution mechanism with a quantum-based parallel processing system that achieves both high search quality and fast convergence.
Solution Approach 2:
The patent introduces dynamic quantum rotating gate update mechanisms that adaptively adjust rotation angles based on fitness differences between chromosomes. This dynamic adjustment allows the algorithm to efficiently explore the search space while maintaining fast convergence, resolving the contradiction between thorough search and speed by making the evolution process adaptive rather than static.
2Reliability
If the population size is increased to expand search space, then the reliability of results is improved, but the number of computations increases and search efficiency decreases
Solution Approach 1:
The patent substitutes the classical population evolution mechanism with quantum parallel computing using P*G*C qubits to represent the population. This quantum mechanical approach allows simultaneous representation and processing of multiple chromosomes, achieving comprehensive search space coverage without the linear increase in computational burden characteristic of classical methods.
Solution Approach 2:
The patent transitions from classical bit-based chromosome representation to quantum qubit-based representation, adding a quantum superposition dimension. This dimensional change allows the algorithm to explore the search space more efficiently by utilizing quantum parallelism, achieving better search coverage with reduced computational resources compared to classical approaches.
3Reliability
If the code length of binary-phase-coded radar signal is increased to improve performance, then the anti-interference ability is improved, but the search process becomes more complicated and time-consuming
Solution Approach 1:
The patent replaces the classical exhaustive enumeration search method with a quantum genetic algorithm that uses quantum parallel computing. This substitution enables efficient searching of long code-length signal spaces by utilizing quantum superposition and entanglement, achieving comprehensive search coverage for high-performance signals without the exponential time increase that plagues classical methods.
Solution Approach 2:
The patent introduces dynamic quantum rotating gate operations that adaptively evolve chromosomes toward optimal solutions. This dynamic evolution mechanism efficiently navigates the complex search space of long code-length signals by continuously adjusting rotation angles based on fitness feedback, reducing search time while maintaining the ability to find high-performance signals with strong anti-interference capabilities.
Data Source
AI summary
The application discloses a signal determination method based on a quantum genetic algorithm, including: constructing qubits based on the number and length of phase-coded radar signals transmitted by a radar system and the number of chromosomes; determining a gene sequence of the first chromosome based on all the qubits; judging whether there exists a first chromosome that satisfies a preset termination condition; if yes, taking the first chromosome that satisfies a preset termination condition as a phase-coded radar signal transmitted by the radar system; if no, updating all the first chromosomes based on the mutation probability, a preset crossover strategy, a quantum catastrophe strategy and the rotation angle to obtain second chromosomes; and replacing all the first chromosomes in each of the populations with all the second chromosomes, proceeding to the judgment step, and ending the operation until a termination condition is met.