Mr. Anpeng Song Profile

Anpeng Song

SPIE Involvement:

Author

Publications (2)

This will count as one of your downloads.

You will have access to both the presentation and article (if available).

DOWNLOAD NOW

This content is available for download via your institution's subscription. To access this item, please sign in to your personal account.

Email or Username Forgot your username?

Password Forgot your password?

Show

Keep me signed in

No SPIE account? Create an account

Proceedings Article | 30 April 2024 Paper

Motion compensation imaging algorithm for inverse synthetic aperture LiDAR of complex moving targets

Jian Li, Kai Jin, Chen Xu, Anpeng Song, Shengqian Wang

Proceedings Volume 13156, 1315616 (2024) https://doi.org/10.1117/12.3018208

Read Abstract +

The inverse synthetic aperture LiDAR (ISAL) system demonstrates excellent performance in various application scenarios, including long-range target imaging and recognition. However, due to the micrometer scale of the ISAL system carrier, compensating for the motion error of high-speed complex motion targets becomes challenging. Linear frequency modulation (LFM) signals are not enough to describe these targets accurately, as they can be better represented by high-order polynomial phase signals. Nevertheless, the presence of second-order and higher phase components can greatly affect the coherent synthesis between pulses. To tackle this issue, we propose a non-searching fast cubic phase signal estimation algorithm based on the fourth-order instantaneous autocorrelation function. This algorithm aims to estimate the second-order and third-order coefficients of the rotational error signals using the non-uniform Fourier transform. By accounting for advection compensation, we model the phase of the signal of the complex motion target as the third-order form of the slow time. The Fourier transform of the fourth-order instantaneous autocorrelation function presents challenges, such as the nonlinear coupling between the slow time and delay time, as well as the nonuniform sampling of the delay time. We suggest utilizing the nonuniform Fourier transform to complete the two-dimensional transformation and estimate the obtained second-order and third-order coefficients. In comparison to the traditional range doppler (RD) algorithm, our proposed algorithm achieves better image point focusing and enhances the energy aggregation of scattering points by approximately four times. Simulation results validate the effectiveness of this algorithm.

SPIE Journal Paper | 22 September 2023

Adaptive motion error compensation method based on bat algorithm for maneuvering targets in inverse synthetic aperture LiDAR imaging

Jian Li, Kai Jin, Chen Xu, Anpeng Song, Dengfeng Liu, Hao Cui, Shengqian Wang, Kai Wei

OE, Vol. 62, Issue 09, 093103, (September 2023) https://doi.org/10.1117/12.10.1117/1.OE.62.9.093103

KEYWORDS: Error analysis, Motion models, Detection and tracking algorithms, Mathematical optimization, Optical engineering, Particle swarm optimization, Pulse signals, Doppler effect, Signal detection, Synthetic aperture radar

Read Abstract +

Motion error compensation is a crucial aspect of processing inverse synthetic aperture light detection and ranging data. Motion phase error occurs mainly due to the relative motion between the target and the system, as well as vibration of either the system or the target, which significantly affects the image quality of optical synthetic aperture radar. Since spatial targets usually have a non-cooperative motion state with a high degree of motion parameter uncertainty, accurate estimation of cross-range phase error becomes challenging due to the presence of envelope tilt effect. We propose an adaptive compensation method that handles motion errors of maneuvering targets by estimating and compensating various types of errors introduced by the target motion process. Using the geometric and signal models to analyze error components, a compensation model is established that uses envelope contrast and image entropy as fitness functions. The bat algorithm is employed to solve this error model. Simulation and outdoor experimental results demonstrate that the proposed algorithm offers higher accuracy and better stability compared to traditional optimization algorithms.

My Library

You currently do not have any folders to save your paper to! Create a new folder below.

Folder Name

Folder Description

View contact details

UPDATE YOUR PROFILE

Is this your profile? Update it now.

Sign into your SPIE.org account

Don’t have a profile and want one?

Create an account on SPIE.org

Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks. You are receiving this notice because your organization may not have SPIE eBooks access.*

*Shibboleth/Open Athens users─please sign in to access your institution's subscriptions.

To obtain this item, you may purchase the complete book in print or electronic format on SPIE.org.

ORGANIZATIONAL
Sign in with credentials provided by your organization.

Organizational Username

Organizational Password

Show/Hide Password

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members:

Non-members: ADD TO CART

Keywords/Phrases

Search In:

Publication Years