Joint time delay and Doppler stretch estimation using wideband signals

Jin, Qu; Davidson, T.N.; Luo, Zhi-Quan

doi:10.1109/ssap.1992.246838

Cited by 15 publications

(20 citation statements)

References 4 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Under a similar condition, [22] proves that increasing the effective time-bandwidth product can improve the joint estimation accuracy of the time delay and the Doppler stretch. Nevertheless, how the waveform parameters affect the CRLB of the time delay as well as the CRLB of the Doppler stretch are not considered separately.…”

Section: Introductionmentioning

confidence: 79%

“…For a wideband model, when the target has only a point scatterer, the wideband ambiguity function (WBAF), which is the counterpart of the AF, is employed [13], [22], [33]. It is shown in [22] that under high SNRs, the WBAF estimator is asymptotically unbiased and the variances are close to the CRLBs for a large variety of signals. In this section, we examine the performance of the WBAF-based estimator for an extended target.…”

Section: Discussion On Waveform Parameters In the General Casementioning

confidence: 99%

“…[1]- [5] and references therein), while the counterpart for wideband signals has received less attention. Specifically, [19], [22] concern the CRLB for a general wideband signal along with a single scatterer model. Exploiting an extended target model, [26] consider the CRLBs of the velocity and HRR profiles estimation with a step frequency signal.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Cramer-Rao lower bounds of joint delay-Doppler estimation for an extended target

Zhao¹,

Huang²

2015

2015 IEEE Global Conference on Signal and Information Processing (GlobalSIP)

View full text Add to dashboard Cite

Section: Introductionmentioning

confidence: 79%

Section: Discussion On Waveform Parameters In the General Casementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Cramer-Rao lower bounds of joint delay-Doppler estimation for an extended target

Zhao¹,

Huang²

2015

2015 IEEE Global Conference on Signal and Information Processing (GlobalSIP)

View full text Add to dashboard Cite

“…The source range is approximately 300 m in the examples, the sensor is located at the origin x o = (0, 0), the speed of sound is c = 335 m/s, and the source speed is V n = 0.2c (for all n). We assume that N Doppler-shift measurements are available at the sensor according to the model (6). Each ∆f n is assumed to be estimated at the sensor by processing a segment of acoustic time-series data with length T 1 .…”

Section: Examplesmentioning

confidence: 99%

“…Assuming an additive Gaussian noise channel with variance N 0 , the CRB on estimation of γ 0 is [6] var(γ 0 ) ≥ γ 0 N 0 2|a| 2 β,…”

Section: Combining Tde and Dopplermentioning

confidence: 99%

Multi-Modal Sensor Localization Using a Mobile Access Point

Sadler

Kozick²,

Tong³

Proceedings. (ICASSP '05). IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005.

View full text Add to dashboard Cite

We consider the problem of sensor node localization in a randomly deployed sensor network, using a mobile access point (AP). The mobile AP can be used to localize many sensors simultaneously in a broadcast mode, without a preestablished sensor network. We consider a multi-modal approach, combining radio and acoustics. The radio broadcasts timing, location information, and acoustic signal parameters. The acoustic emission may be used at the sensor to measure Doppler stretch, time delay, and angle of arrival. These measurements are individually sufficient to localize a sensor node, or they may be advantageously combined. We focus on the cases of Doppler and time delay. Sensor localization algorithms are developed, and performance analysis includes acoustic propagation effects caused by the turbulent atmosphere.

show abstract

Signal Processing for Large Bandwidth and Long Duration Waveform SAR

Lin

Zeng

et al. 2003

Radar Signal Processing and Its Applications

View full text Add to dashboard Cite

Abstract. We first show that for some kinds of signals a ''bandwidth and time duration reduction technique'' can be used to simulate waveform distortions caused by moving targets, that is, it is correct to measure the waveform distortions at very large TB with relatively small by reducing TB and increasing while keeping TB unchanged, where T is the duration of the transmitted signal, B is the bandwidth and is the relative speed of targets. We then study the waveform distortions in SAR signals caused by moving antenna. Based on the bandwidth and time duration reduction technique, a lot of time and memory are saved in simulations. We then confirm by simulations that waveform distortions do pose problems when processing very large bandwidth and long duration SAR data using conventional SAR processing methods. Finally we propose the concepts of wideband and narrowband processing of SAR data. Models are set up for wideband and narrowband SAR data processing, and new methods are presented for reconstructing targets using the proposed models. Simulations show that the methods can improve the quality of the simulated SAR images.

show abstract

Joint time delay and Doppler stretch estimation using wideband signals

Cited by 15 publications

References 4 publications

Cramer-Rao lower bounds of joint delay-Doppler estimation for an extended target

Cramer-Rao lower bounds of joint delay-Doppler estimation for an extended target

Multi-Modal Sensor Localization Using a Mobile Access Point

Signal Processing for Large Bandwidth and Long Duration Waveform SAR

Contact Info

Product

Resources

About