MIMO radar single measurement vector DOA estimation method based on iterative weighted near-end projection

An iterative weighting, radar technology, applied in the field of multi-input multi-output radar target parameter estimation, which can solve the problems of DOA estimation performance degradation and DOA estimation performance not being optimal.

Active Publication Date: 2019-09-20
NANJING UNIV OF INFORMATION SCI & TECH
View PDF4 Cites 14 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, the algorithm needs to predict the prior information of the number of targets when calculating the weighted vector. When the wrong judgment of the number of targets will lead to the decline of the DOA estimation performance of the algorithm
The above uses the SL0 algorithm and l 1 -In the method of SVD algorithm

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
  • MIMO radar single measurement vector DOA estimation method based on iterative weighted near-end projection
  • MIMO radar single measurement vector DOA estimation method based on iterative weighted near-end projection
  • MIMO radar single measurement vector DOA estimation method based on iterative weighted near-end projection

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0062] The technical solutions of the present invention will be described in detail below in conjunction with specific embodiments and accompanying drawings.

[0063] Such as figure 1 As shown, a MIMO radar single-measurement vector DOA estimation method based on iterative weighted near-end projection includes the following steps:

[0064] Step 1: Assume that the narrowband monostatic MIMO radar system has M transmitting array elements and N receiving array elements, the transmitting and receiving arrays are uniform linear arrays, and the array element spacing is d t = λ / 2 and d r =λ / 2, where λ is the wavelength of the received signal. Suppose there are P far-field narrow-band incoherent targets, and their incident angles are θ 1 ,θ 2 ,...,θ P , the MIMO radar receiving array signal can be expressed as:

[0065] x(t)=As(t)+n(t) (1)

[0066] In the formula, is the transmit-receive joint steering matrix, where is the steering vector of the transmitting array, is the...

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 MIMO (Multiple Input and Multiple Output) radar single measurement vector DOA (Direction of Arrival) estimation method based on iterative weighted near-end projection. The method comprises the following steps of: vectorizing a covariance matrix of received data after dimensionality reduction; constructing a weighting matrix by using high-order power of a covariance inverse matrix after dimensionality reduction so as to perform proper weight constraint on a sparse vector; establishing a weighted near-end function optimization model to represent a non-convex and non-smooth sparse optimization problem in MIMO radar single measurement vector DOA estimation; and finally, obtaining a near-end operator through an SCAD (Smoothly Clipped Absolute Deviation Penalty) function in an iteration process, and projecting the near-end operator to a feasible set to solve the weighted function optimization model so as to obtain a sparse solution, and obtaining a real target DOA estimation value by searching the position of a spectral peak. Compared with a reweighted l1-SVD algorithm and a weighted SL0 (Smoothed l0norm) algorithm, the method can obtain the better DOA estimation performance, and the prior information of the number of the targets is not needed to be known in advance.

Description

technical field [0001] The invention relates to the field of multiple-input multiple-output (MIMO) radar target parameter estimation, in particular to a DOA estimation method for MIMO radar single-measurement vectors based on iterative weighted near-end projection. Background technique [0002] Multiple Input and Multiple Output (MIMO) radar system is a new radar system proposed in recent years. Compared with phased array radar, MIMO radar is more effective in target detection, anti-jamming, target parameter estimation and target recognition. It has potential advantages and thus has attracted widespread attention. MIMO radar uses multiple transmitting antennas to simultaneously transmit mutually orthogonal signals at the transmitting end, and uses multiple receiving antennas at the receiving end to receive echo signals and process them with matched filters, thereby expanding the aperture of the MIMO radar array. According to different configurations of transceiver arrays, M...

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): G01S7/41G01S3/14
CPCG01S7/418G01S3/143
Inventor 陈金立郑瑶李家强
Owner NANJING UNIV OF INFORMATION SCI & TECH
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

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

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap