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

Improved ML (maximum likelihood) skywave radar maneuvering target parameter estimation method

A technique for maneuvering targets and parameter estimation, which is applied in radio wave measurement systems, radio wave reflection/re-radiation, and utilization of re-radiation, etc. It can solve the problems of inaccurate inversion results and increased computational complexity

Inactive Publication Date: 2016-06-15
UNIV OF ELECTRONIC SCI & TECH OF CHINA
View PDF5 Cites 10 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] At present, the ML method has not been applied to the parameter estimation of sky-wave radar maneuvering targets, and the traditional ML algorithm needs to perform matrix inversion operation, which increases the complexity of the operation, and in the case of a singular matrix, the inversion result will be inaccurate

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
  • Improved ML (maximum likelihood) skywave radar maneuvering target parameter estimation method
  • Improved ML (maximum likelihood) skywave radar maneuvering target parameter estimation method
  • Improved ML (maximum likelihood) skywave radar maneuvering target parameter estimation method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0064] Embodiment 1: Assume that the carrier frequency of the sky-wave radar is 14.768 MHz, the pulse repetition period is 12 ms, and the number of sampling points is 512. The motion parameters of the maneuvering target are set as follows: the initial speed of the maneuvering target is 100m / s, and the initial acceleration is 20m / s 2 And the initial acceleration change rate is 3m / s 3 . The signal-to-noise ratio is set to -20dB~20dB, and 100 Monte Carlo experiments are performed under each signal-to-noise ratio, and the normalized mean square error of the parameter to be estimated is taken Compare with CRB and draw a graph.

[0065]Fig. 1 shows the present invention, HAF method (specifically see literature: Enhanced visibility of maneuvering targets for high-frequency over-the-horizon radar [J]. KunLuandXingzhaoLiu.IEEETransactiononAntennasandPropagation, 2005,53 (1): 404-411), CPF (Cubicphase function) and CPF method ( For details, see the literature: 3-orderpolynomialphase...

Embodiment 2

[0066] Embodiment 2: Assume that there are two maneuvering targets in the signal received by the sky-wave radar, and their initial speeds are: v 1 = 100m / s and v 2 =-200m / s, the initial acceleration is: a 1 =20m / s 2 and a 2 =10m / s 2 , initial acceleration rate of change: η 1 =3m / s 3 and η 2 =5m / s 3 . The sky-wave radar carrier frequency is 14.768MHz, the pulse repetition period is 12ms, and the number of sampling points is 512. Figure 2-a is the normalized Doppler spectrum of the sky-wave radar received signal (x(n)=s(n)+c(n)+w(n), n=1,2,...,512); Figure 2-b is the normalized Doppler spectrum of the received signal (x(n)=s(n)+w(n),n=1,2,…,512) of the sky-wave radar after sea clutter suppression; Figure 2-c It is the Doppler frequency spectrum of the maneuvering target after estimating the motion parameters of the maneuvering target and performing Doppler compensation in the present invention.

[0067] From Figure 2-a It can be seen that the signal-to-noise rati...

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 discloses an improved ML (maximum likelihood) skywave radar maneuvering target parameter estimation method and belongs to the radar communication technical field. According to the method, the maneuvering target signals of a skywave radar are modeled into a generalized phase polynomial; and a received signal likelihood function is maximized, so that the parameter estimation of a maneuvering target can be realized. In order to avoid matrix inversion computation in a traditional likelihood function, the maximization problem of the likelihood function is converted into the optimization problem of overdetermination nonlinear least square estimation, so that high-precision maneuvering target parameter estimation under a low signal to noise ratio can be realized. Compared with a traditional maneuvering target parameter estimation algorithm, the method of the invention can not only achieve higher-accuracy parameter estimation under a lower signal to noise ratio, but also can estimate the motion parameters of a plurality of maneuvering targets simultaneously.

Description

technical field [0001] The invention belongs to the technical field of communication radar, in particular to a method for estimating parameters of maneuvering targets of sky-wave radar with low input signal-to-noise ratio and high precision. Background technique [0002] Sky-wave over-the-horizon radar (OTHR, over-the-horizon radar) uses the ionosphere's reflection of high-frequency electromagnetic waves to detect targets from top to bottom, so as to achieve over-the-horizon detection of ships, aircraft and other targets. However, due to the long working distance and complex working environment of sky-wave radar rays, the signal attenuation is serious during the transmission process, and the target energy is often weak, which is not conducive to target detection. In addition, in order to obtain high Doppler resolution, sky-wave radar usually adopts a long coherent integration time (CIT, coherent integration time), and the coherent integration time is generally as long as ten...

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
IPC IPC(8): G01S13/72G01S7/36
CPCG01S7/36G01S13/726
Inventor 胡进峰陈汉文薛长飘胡天威段杰谢浩
Owner UNIV OF ELECTRONIC SCI & TECH OF CHINA
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