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Parameterized-sparse-representation-based single-bit target time delay estimation method of compressed sensing radar

A technology of time delay estimation and sparse representation, applied in the field of radar target parameter estimation

Active Publication Date: 2018-10-02
NANJING UNIV OF SCI & TECH
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AI Technical Summary

Problems solved by technology

However, since the single-bit sampling value is a nonlinear measurement of the echo signal, the time delay estimation method for off-grid targets based on linear measurements in traditional compressive sensing radar cannot be directly applied

Method used

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  • Parameterized-sparse-representation-based single-bit target time delay estimation method of compressed sensing radar
  • Parameterized-sparse-representation-based single-bit target time delay estimation method of compressed sensing radar
  • Parameterized-sparse-representation-based single-bit target time delay estimation method of compressed sensing radar

Examples

Experimental program
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Effect test

Embodiment

[0106] The example is simulated by Matlab software:

[0107] 1. Simulation system parameter setting

[0108] The transmitted signal bandwidth is B=50MHz, the pulse width T=20μs, and the Nyquist sampling rate is f s =100MHz, delay resolution is Δ τ =0.01μs, sampling number N t =4000, M=1000, the real target delay is distributed in the interval [0,T d ) range, T d =1 μs, the number of atoms in the discrete grid dictionary is N=100.

[0109] 2. Simulation target parameter setting

[0110] Suppose there are 3 targets in the scene, their reflection coefficients are all 1, and the time delay is [1.6766; 74.7075; 95.7591]Δ τ . In order to effectively evaluate the performance of the algorithm, this paper uses Δ τ normalizes the delay estimation error, so we use

[0111]

[0112] To measure the target delay estimation error, the number of Monte Carlo simulation experiments is 200 times, and ε=0.001 in the iteration stop condition. It is worth mentioning that due to quantiz...

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Abstract

The invention discloses a parameterized-sparse-representation-based single-bit target time delay estimation method of a compressed sensing radar. The method comprises: a possible delay range of a target is discretized; on the basis of a Taylor interpolation method, parameterized sparse representation of a radar echo is carried out at a nearest neighbor delay grid of the target; a single-bit compressed sensing model is constructed; a nearest neighbor delay grid of the target is calculated based on a single-bit compressed sensing sparse reconstruction algorithm; and according to an alternate optimization method, an offset value between the target delay and a nearest neighbor discrete grid and a target reflection coefficient are estimated to complete target delay parameter estimation. Therefore, problems of slow sampling rate, complicated quantization structure and high power consumption of the traditional compressed sensing radar re solved effectively, so that the cost is lowered and thesampling efficiency is improved. Meanwhile, the BIHT algorithm has the low computational complexity; the delay estimation precision obtained by the convex optimization method is high; and the anti-noise performance is good.

Description

technical field [0001] The invention belongs to the field of radar target parameter estimation, and in particular relates to a single-bit compressed sensing radar target time delay estimation method based on parameterized sparse representation. Background technique [0002] Compressed Sensing (CS) theory can sample sparse signals at a sampling rate much lower than the Nyquist rate, and reconstruct the signal through the sparse regular optimization method, and collect and process broadband / ultra-wideband signals is of great significance. At present, the theory is applied in many fields such as medical imaging, pattern recognition, optical imaging, and radar remote sensing. [0003] Compressed sensing theory usually assumes that compressed sampling values ​​have infinitely high precision, but in practical application scenarios, compressed sampling values ​​must be quantized before transmission and storage. Quantization is an irreversible nonlinear operation in the digitizati...

Claims

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Application Information

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IPC IPC(8): G01S7/41
CPCG01S7/411
Inventor 尹佳薛城陈胜垚席峰
Owner NANJING UNIV OF SCI & TECH
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