Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  have developed an improved solution of a maximum likelihood (ML)-based multitarget tracking problem by introducing a more accurate angular difference representation across the Riemann sheet into the Gauss-Newton's descend-direction relaxation routine obtaining a semi-optimal solution through shorter paths in the search space which eliminates the unnecessary relaxation calculations due to potential miss-assignments among the given and estimated measurements.  have proved that a new O(N2) 2-D data assignment algorithm based on the rotational sorting of angles maximizes the conditional likelihood function with respect to data association for fixed target states. The improved performance has been verified by implementing the improved tracking algorithm by a decentralized cooperative scheme 1,2,3, one with the present angular formula and the other with the conventional formula used in Chen and Tokuda [2, 3] which is about twice slor even if it has a better O(N log N) complexity data assignment routine. The number of iterations needed has been reduced from an average of 39.2 to 17.3 iterations with the new formula, halving the computational time from 56 seconds to 32 seconds.
['Liang Chen', 'Naoyuki Tokuda']
I am writing a research paper on a idea AN IMPROVED SOLUTION TO ML-BASED MULTITARGET MOTION TRACKING WITH BEARINGS-ONLY MEASUREMENTS
[{"from": "human", "value": "I am writing a research paper on a idea AN IMPROVED SOLUTION TO ML-BASED MULTITARGET MOTION TRACKING WITH BEARINGS-ONLY MEASUREMENTS"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  have developed an improved solution of a maximum likelihood (ML)-based multitarget tracking problem by introducing a more accurate angular difference representation across the Riemann sheet into the Gauss-Newton's descend-direction relaxation routine obtaining a semi-optimal solution through shorter paths in the search space which eliminates the unnecessary relaxation calculations due to potential miss-assignments among the given and estimated measurements.  have proved that a new O(N2) 2-D data assignment algorithm based on the rotational sorting of angles maximizes the conditional likelihood function with respect to data association for fixed target states. The improved performance has been verified by implementing the improved tracking algorithm by a decentralized cooperative scheme 1,2,3, one with the present angular formula and the other with the conventional formula used in Chen and Tokuda [2, 3] which is about twice slor even if it has a better O(N log N) complexity data assignment routine. The number of iterations needed has been reduced from an average of 39.2 to 17.3 iterations with the new formula, halving the computational time from 56 seconds to 32 seconds."}]