The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.
Target Detection and Localization Using MIMO Radars and Sonars
Abstract
In this paper, we propose a new space-time coding configuration for target detection and localization by radar or sonar systems. In common active array systems, the transmitted signal is usually coherent between the different elements of the array. This configuration does not allow array processing in the transmit mode. However, space-time coding of the transmitted signals allows to digitally steer the beam pattern in the transmit in addition to the received signal. The ability to steer the transmitted beam pattern, helps to avoid beam shape loss. We show that the configuration with spatially orthogonal signal transmission is equivalent to additional virtual sensors which extend the array aperture with virtual spatial tapering. These virtual sensors can be used to form narrower beams with lower sidelobes and, therefore, provide higher performance in target detection, angular estimation accuracy, and angular resolution. The generalized likelihood ratio test for target detection and the maximum likelihood and Cramer-Rao bound for target direction estimation are derived for an arbitrary signal coherence matrix. It is shown that the optimal performance is achieved for orthogonal transmitted signals. Target detection and localization performances are evaluated and studied theoretically and via simulations
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Fundamentals of Statistical Signal Processing: Estimation Theory
Sengijpta, S. K. (1995) · Technometrics · doi:10.1080/00401706.1995.10484391 · Cited by 11,076
Fundamentals of statistical signal processing: Estimation theory
Prasad, K. V. (1994) · Control Engineering Practice · doi:10.1016/0967-0661(94)90195-3 · Cited by 7,902
Kronecker Products and Matrix Calculus: With Applications
Graham, A. (1981) · CERN Document Server (European Organization for Nuclear Research) · Cited by 1,630
MIMO radar: an idea whose time has come
Fishler, E., Haimovich, A., Blum, R., Chizhik, D., Cimini, L., & Valenzuela, R. (2004) · Proceedings of the 2004 IEEE Radar Conference (IEEE Cat. No.04CH37509) · doi:10.1109/nrc.2004.1316398 · Cited by 1,453
(1993) · Springer Series in Information Sciences · doi:10.1007/978-3-642-77347-1 · Cited by 276
On the achievable DF accuracy of two kinds of active interferometers
Messer, H., Singal, G., & Bialy, L. (1996) · IEEE Transactions on Aerospace and Electronic Systems · doi:10.1109/7.532277 · Cited by 17
Cited by
Joint Transmit Beamforming for Multiuser MIMO Communications and MIMO Radar
Liu, X., Huang, T., Shlezinger, N., Liu, Y., Zhou, J., & Eldar, Y. C. (2020) · IEEE Transactions on Signal Processing · doi:10.1109/tsp.2020.3004739 · Cited by 992
Cramér-Rao Bound Optimization for Joint Radar-Communication Beamforming
Liu, F., Liu, Y.-F., Li, A., Masouros, C., & Eldar, Y. C. (2022) · IEEE Transactions on Signal Processing · doi:10.1109/tsp.2021.3135692 · Cited by 774
Hassanien, A., Amin, M. G., Zhang, Y. D., & Ahmad, F. (2016) · IEEE Transactions on Signal Processing · doi:10.1109/tsp.2015.2505667 · Cited by 641
Bilik, I., Longman, O., Villeval, S., & Tabrikian, J. (2019) · IEEE Signal Processing Magazine · doi:10.1109/msp.2019.2926573 · Cited by 374
Self-citation
Metadata
- Authors
- Bekkerman, I., & Tabrikian, J.
- Venue
- IEEE Transactions on Signal Processing
- Published
- 2006-10
- Volume
- 54
- Issue
- 10
- Pages
- 3873-3883
- ISSN
- 1053-587X (ISSN-L)
- OpenAlex
- W2171576754
- Cited by
- 1,259
- References
- 6
- FWCI
- 71.37
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Target Detection and Localization Using MIMO Radars and Sonars. https://app.cochat.ai/papers/10.1109/tsp.2006.879267
- The paper
- Bekkerman, I., & Tabrikian, J. (2006). Target Detection and Localization Using MIMO Radars and Sonars. IEEE Transactions on Signal Processing. https://doi.org/10.1109/tsp.2006.879267
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.