Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

A Robust Sidelobe Suppression Method for Cognitive Radar Based on Sequence Optimization

A cognitive radar and sidelobe suppression technology, applied in radio wave measurement systems, instruments, etc., can solve problems such as making full use of unfavorable information to correct errors in time, unsatisfactory extraction of weak and small targets, and lack of pertinence in sidelobe suppression. Effects of improved sidelobe suppression, improved robustness to noise, and improved perception

Active Publication Date: 2022-07-29
SHIJIAZHUANG TIEDAO UNIV
View PDF0 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] 1. Using a mismatch filter for sidelobe suppression, this method is at the cost of a certain signal-to-noise ratio loss, and the suppression effect is limited
2. The CLEAN algorithm estimates the position of the large target and removes the influence of the distance side lobe of the large target. The extraction effect of the algorithm for the weak and small targets is not ideal
However, this method is an overall estimate of TIR, lacks pertinence in sidelobe suppression, and is not conducive to the full use of information and timely correction of errors

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • A Robust Sidelobe Suppression Method for Cognitive Radar Based on Sequence Optimization
  • A Robust Sidelobe Suppression Method for Cognitive Radar Based on Sequence Optimization
  • A Robust Sidelobe Suppression Method for Cognitive Radar Based on Sequence Optimization

Examples

Experimental program
Comparison scheme
Effect test

Embodiment

[0079] In order to verify the effectiveness and superiority of the method of the present invention, the APC method and the EBD method were compared and analyzed with the method of the present invention from the aspects of imaging accuracy, algorithm convergence and anti-noise robustness through the following two sets of simulation experiments. In the experiment, the emission waveform used in the APC method is the M sequence with N=40, which is used as the initial emission waveform in the EBD method and the method of the present invention. Taking the SR-71 reconnaissance aircraft as the target to be estimated, it contains L=20 range units in total, and its one-dimensional high-resolution range image is as follows figure 2 shown. Noise covariance matrix in represents the noise power.

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention relates to a method for robust side lobe suppression of cognitive radar based on sequence optimization. Optimal transmit waveform and receive filter; use the cyclic optimization method to solve the objective function, so that the sidelobe suppression performance meets the preset requirements: for the l-th range resolution unit, solve the joint optimization problem of transmit waveform and receive filter, In each iteration, the joint optimization problem is decomposed into two independent optimization problems: ①Fixed waveform to optimize the receiving filter ②Optimize the waveform on the basis of the known filter The present invention adjusts the transceiver system according to the scene information fed back in real time, effectively Improves the radar's ability to sense the environment, thereby improving the sidelobe suppression performance and improving the robustness against noise.

Description

technical field [0001] The present invention relates to a cognitive radar side lobe suppression method, in particular to a cognitive radar robust side lobe suppression method based on sequence optimization. Background technique [0002] With the increase of radar signal bandwidth and resolution, the target echo model becomes a multi-scattering center model. When there are targets in adjacent positions in the range image, the output of the matched filter may appear: 1) Strong target side lobes cover up weak targets; 2) a large number of false targets. How to achieve effective suppression of range side lobes is the key to improving radar detection performance, especially the detection performance of weak targets. In order to solve this problem, the following methods are often used in the prior art: [0003] 1. The mismatch filter is used for sidelobe suppression. This method costs a certain loss of signal-to-noise ratio, and the suppression effect is limited. 2. The CLEAN a...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
Patent Type & Authority Patents(China)
IPC IPC(8): G01S7/28
CPCG01S7/2813
Inventor 庄珊娜金松坡
Owner SHIJIAZHUANG TIEDAO UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com