Method for optimizing maximum MI waveforms of cognition radar based on IGA-NP algorithm

Abstract

The invention discloses a method for optimizing maximum MI waveforms of the cognition radar based on an IGA-NP algorithm. The method comprises steps of determining the cognition radar, wherein target signals exist in a detection range of the cognition radar, carrying out calculation to obtain target signal spectrum variance, clutter spectrum variance and a noise power spectrum and setting a to-be-optimized waveform power spectrum; determining an energy constraint condition of the to-be-optimized waveforms and carrying out problem modeling; setting iteration times and carrying out integar algebras of non-linearity programming optimization; setting the number of chromosomes, the crossover probability and the mutation probability; calculating an initial population Code; carrying out initialization: making h represent the hth iteration, wherein h belongs to {1, 2,..., G}, and G represents the set biggest evolution algebra and calculating the iterated k-opt searching population shown in the description and the optimal chromosome after the hth iteration; and finishing the iteration until the h=G, and using the corresponding optimal chromosome when the iteration is stopped as the global optimal chromosome, wherein the global optimal chromosome is the to-be-optimized waveform power spectrum.

Description

technical field [0001] The invention belongs to the field of radar technology, in particular to a cognitive radar maximum MI waveform optimization method based on the IGA-NP algorithm, that is, a cognitive algorithm based on the Improved Genetic Algorithm-Nonlinear Programming (IGA-NP) algorithm The radar maximum mutual information (Mutual Information, MI) waveform optimization method is suitable for the optimization of cognitive radar maximum mutual information waveform under the background of clutter and noise. Background technique [0002] Cognitive radar is to feed back the information extracted from the echo signal to the transmitter by learning the target and the environment. The transmitter adaptively optimizes the design of a new transmission signal according to the environmental information to adapt it to the environment to improve the radar detection performance. This makes the entire cognitive radar system form a closed-loop system. According to the knowledge of ...

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Problems solved by technology

[0004] For the deficiencies in the above-mentioned prior art, the object of the present invention is to propose a method for optimizing the maximum MI waveform of cognitive radar based on the IGA-NP algorithm. Adaptive to variable environment, which can maximize the mutual information of the target and the echo signal under the energy constraints of the cognitive radar transmission signal, and take the prior knowledge of the environment as a reference, and combine the improved genetic algorithm with real number coding with nonlinear programming (ImproveGenetic The Algorithm-Nonlinear Programming (IGA-NP) algorithm searches out the power spectrum of the cognitive radar transmission signal that maximizes the mutual information between the target and the echo signal, and improves the problem that the target is not easy to detect in the background of clutter and noise, thereby improving the detection performance of the target.

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