A Novel Moving Target Detection Approach for Dual-Channel Sar System

Tian, Bin; Zhu, Daiyin; Zhu, Zhaoda

doi:10.2528/pier10120107

Cited by 45 publications

(38 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…To improve the penetrability of nonmetallic obstacle, ultra-wideband (UWB) radar has been employed to detect vital sign of the victims in the NLOS scenes [9][10][11][12][13][14][15][16]. In these scenes, it mainly focuses on whether the victim is alive [16][17][18][19][20][21][22][23], namely life detection. It is realized based on accumulation of energy in a period of time, and signal-to-noise ratio (SNR) of vital sign can be improved.…”

Section: Introductionmentioning

confidence: 99%

A New Method for Non-Line-of-Sight Vital Sign Monitoring Based on Developed Adaptive Line Enhancer Using Low Centre Frequency Uwb Radar

Li¹,

Zhao²,

Lv³

et al. 2013

PIER

View full text Add to dashboard Cite

Abstract-The physiological parameters monitoring of human target are considered to be a meaningful and challenging task in non-lineof-sight (NLOS) scenes such as rescue of trapped survivors in postdisaster. In this paper, a new method based on developed adaptive line enhancer (DALE) is proposed to monitor vital signs via ultra-wideband (UWB) radar with centre frequency of 400 MHz. The validity of this new method is proved by means of two experiments with different positions of human target. The good results demonstrate that this new method can be used for vital sign monitoring including respiration and heartbeat through the obstacle. Furthermore, the motion responses due to respiration and heartbeat in different body positions are also discussed.

show abstract

Section: Introductionmentioning

confidence: 99%

A New Method for Non-Line-of-Sight Vital Sign Monitoring Based on Developed Adaptive Line Enhancer Using Low Centre Frequency Uwb Radar

Li¹,

Zhao²,

Lv³

et al. 2013

PIER

View full text Add to dashboard Cite

show abstract

“…It is reported that typical sensor platforms is able to provide wide area search coverage (approximately 100 km 2 area per minute) at 1.0 m × 1.0 m resolution [6]. This attractive capability has opened new interesting research fields in both civil and military contexts, such as target detection [7,8], target recognition [9,10], navigation [11], etc.. Target detection is one of the core applications of SAR remote sensing and has received considerable attentions in the recent years, such as CFAR method [12][13][14][15][16][17][18], the GLRT method [19], the extended fractal-based method [20], the wavelet transform-based method [21], etc.. Among these kinds of methods, the CFAR method has been most widely used for it is capable of maintaining the constant false alarm probability at a certain level in non-stationary background through an adaptive threshold.…”

Section: Introductionmentioning

confidence: 99%

Cfar Target Detection in Ground Sar Image Based on Kk Distribution

Gao¹,

Zhan²,

Wan³

et al. 2013

PIER

View full text Add to dashboard Cite

Abstract-This paper deals with the problem of constant false alarm rate (CFAR) target detection in high-resolution ground synthetic aperture radar (SAR) images based on KK distribution.For the parameter estimation of KK distribution, the semi-experiential algorithm is analyzed firstly. Then a new estimation algorithm based on the particle swarm optimization (PSO) is proposed, which takes the discrepancies between the histogram of the clutter data and probability density function (PDF) of KK distribution at some selected points as the cost function to search for the optimal parameter values using PSO algorithm. The performance of the two algorithms is compared using Monte-Carlo simulation using the simulated data sets generated under different conditions; and the estimation results validate the better performance of the new algorithm. Then the KK distribution, which is proposed for spiky sea clutter originally, is applied to model the real ground SAR clutter data. The goodness-of-fit test clearly show that the KK distribution is able to model the ground SAR clutter much better than some common used model, such as standard Kdistribution and Gamma, etc. On this basis, a global CFAR target detection algorithm is presented. The detection threshold is calculated numerically through the cumulative density function (CDF) of KK distribution. Comparing the amplitude of every SAR image pixel with this threshold, the potential targets in ground SAR images can be located effectively. Then target clustering is implemented to eliminate the false alarm and obtain more accurate target regions. The detection results of the proposed algorithm in a typical ground SAR image show that it has better performance than the detector based on G 0 distribution.

show abstract

“…Radar has been successfully employed for detection of various entities such as breast cancers [7][8][9], hidden objects or humans [10][11][12][13][14][15][16][17][18][19], moving targets [20][21][22] and their speed [23,24] and speech acquisition [25]. Among various types of radars developed so far, ground penetrating radars (GPRs) have attracted many researchers attention.…”

Section: Introductionmentioning

confidence: 99%

Multi-Feature Based Detection of Landmines Using Ground Penetrating Radar

Park¹,

Park²,

Kim³

et al. 2013

PIER

View full text Add to dashboard Cite

Abstract-In this paper, we present a method for detecting antitank or anti-personnel landmines buried in the ground. A set of data generated by a ground penetrating radar is processed to remove the surface reflection and clutter, yielding signals for possible landmines. In order to detect landmines in the signals, features are computed and compared against a database, which contains those of various landmines. Three features are proposed to use; principal components from principal component analysis, Fourier coefficients and singular values from singular value decomposition method, each of which is chosen to represent each landmine uniquely. Detection is performed using Mahalanobis distance-based method. Examples show that the proposed method can effectively detect landmines in various burial condition.

show abstract

A Novel Moving Target Detection Approach for Dual-Channel Sar System

Cited by 45 publications

References 22 publications

A New Method for Non-Line-of-Sight Vital Sign Monitoring Based on Developed Adaptive Line Enhancer Using Low Centre Frequency Uwb Radar

A New Method for Non-Line-of-Sight Vital Sign Monitoring Based on Developed Adaptive Line Enhancer Using Low Centre Frequency Uwb Radar

Cfar Target Detection in Ground Sar Image Based on Kk Distribution

Multi-Feature Based Detection of Landmines Using Ground Penetrating Radar

Contact Info

Product

Resources

About