Abstract
Controlling the range-Doppler response, i.e. Ambiguity Function (AF) continues to be of great interest in cognitive radar. The design problem is known to be a nonconvex quartic function of the transmit radar waveform. This AF shaping problem becomes even more challenging in the presence of practical constraints on the transmit waveform such as the Constant Modulus Constraint (CMC). Most existing approaches address the aforementioned challenges by suitably modifying or relaxing the design cost function and/or CMC. In a departure from such methods, we develop a solution that involves direct optimization over the non-convex complex circle manifold, i.e. the CMC set. We derive a new update strategy (Quartic-Gradient-Descent (QGD)) that computes an exact gradient of the quartic cost and invokes principles of optimization over manifolds towards an iterative procedure with guarantees of monotonic cost function decrease and convergence. Experimentally, QGD can outperform state of the art approaches for shaping the ambiguity function under CMC while being computationally less expensive.
| Original language | English (US) |
|---|---|
| Title of host publication | 2019 IEEE Radar Conference, RadarConf 2019 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| ISBN (Electronic) | 9781728116792 |
| DOIs | |
| State | Published - Apr 2019 |
| Event | 2019 IEEE Radar Conference, RadarConf 2019 - Boston, United States Duration: Apr 22 2019 → Apr 26 2019 |
Publication series
| Name | 2019 IEEE Radar Conference, RadarConf 2019 |
|---|
Conference
| Conference | 2019 IEEE Radar Conference, RadarConf 2019 |
|---|---|
| Country | United States |
| City | Boston |
| Period | 4/22/19 → 4/26/19 |
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All Science Journal Classification (ASJC) codes
- Computer Networks and Communications
- Signal Processing
- Instrumentation
Cite this
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Ambiguity function shaping via quartic descent on the complex circle manifold. / Alhujaili, Khaled; Monga, Vishal; Rangaswamy, Muralidhar.
2019 IEEE Radar Conference, RadarConf 2019. Institute of Electrical and Electronics Engineers Inc., 2019. 8835538 (2019 IEEE Radar Conference, RadarConf 2019).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
TY - GEN
T1 - Ambiguity function shaping via quartic descent on the complex circle manifold
AU - Alhujaili, Khaled
AU - Monga, Vishal
AU - Rangaswamy, Muralidhar
PY - 2019/4
Y1 - 2019/4
N2 - Controlling the range-Doppler response, i.e. Ambiguity Function (AF) continues to be of great interest in cognitive radar. The design problem is known to be a nonconvex quartic function of the transmit radar waveform. This AF shaping problem becomes even more challenging in the presence of practical constraints on the transmit waveform such as the Constant Modulus Constraint (CMC). Most existing approaches address the aforementioned challenges by suitably modifying or relaxing the design cost function and/or CMC. In a departure from such methods, we develop a solution that involves direct optimization over the non-convex complex circle manifold, i.e. the CMC set. We derive a new update strategy (Quartic-Gradient-Descent (QGD)) that computes an exact gradient of the quartic cost and invokes principles of optimization over manifolds towards an iterative procedure with guarantees of monotonic cost function decrease and convergence. Experimentally, QGD can outperform state of the art approaches for shaping the ambiguity function under CMC while being computationally less expensive.
AB - Controlling the range-Doppler response, i.e. Ambiguity Function (AF) continues to be of great interest in cognitive radar. The design problem is known to be a nonconvex quartic function of the transmit radar waveform. This AF shaping problem becomes even more challenging in the presence of practical constraints on the transmit waveform such as the Constant Modulus Constraint (CMC). Most existing approaches address the aforementioned challenges by suitably modifying or relaxing the design cost function and/or CMC. In a departure from such methods, we develop a solution that involves direct optimization over the non-convex complex circle manifold, i.e. the CMC set. We derive a new update strategy (Quartic-Gradient-Descent (QGD)) that computes an exact gradient of the quartic cost and invokes principles of optimization over manifolds towards an iterative procedure with guarantees of monotonic cost function decrease and convergence. Experimentally, QGD can outperform state of the art approaches for shaping the ambiguity function under CMC while being computationally less expensive.
UR - http://www.scopus.com/inward/record.url?scp=85073120532&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85073120532&partnerID=8YFLogxK
U2 - 10.1109/RADAR.2019.8835538
DO - 10.1109/RADAR.2019.8835538
M3 - Conference contribution
AN - SCOPUS:85073120532
T3 - 2019 IEEE Radar Conference, RadarConf 2019
BT - 2019 IEEE Radar Conference, RadarConf 2019
PB - Institute of Electrical and Electronics Engineers Inc.
ER -