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This paper compares two performance indices for computing optimal observer paths for the bearings-only source localization problem, for constant velocity sources. Previous work on this problem is based on maximizing the determinant of the Fisher information matrix (FIM) of the estimation problem. This paper considers minimizing the trace of a weighted sum of the Cramer-Rao lower bound (CRLB) of current source position error. Quasi-Newton optimization is used to compare optimal observer paths, given the goal of minimizing current position error. Significant differences in optimal paths are observed, arid the CRLB trace is found to yield smaller range error.'The prohleni of li)c,iiting R constait; velocsity 11011-in;trieiiveriiig sourcc rising only bearing rneasrirernmts is known to be tiependcnt on t h : observer's trajectory. Iri a typical c>st,imation problem, a freely rrioving observer rwords bearing inea.surein(;iii.~8 to t,he source through a passive sensor and mtimattts i~lie sourct:'~ unknown position. Alt,lioiigh i~ ~tuniber of authors liavt, studied the tr:ijwtorics that, niakc, this ~)rot)l(*ni ot)sc:rvtible [I-31, the problcni of finding the opt inial o1)scrvcr path has rccr.ivd little iItt>cmtiori. 'lypicdly it is suggested that t,Iics obstmw t>xtv.utes ti t:xtrcmic chiillgo in rlirt,ct,ion for tho hwrings-oiilv locitlizat iori algorit hrns to prforin well. h i i t mort: needs to kx~ siiitf o i i how t,o use observcr trajcctories to improve rstirnatiori &orit lini pcrfortnaim. t,hc> cjur:st,ioii of tiow to properly define optiiriitlity in the bmriiigs-only localization p r o b le~n. The opt,imality criterion iised here is based on minimizing the trace of Crarrit;r-R;to lower bound (CRLB).The CRLB dcfintd in 131 is i'. 1owt.r twund on tht: error covariarice of the estirnatioii 1)robltm. ;tnd gives a criterion of optiniality t lint is indtqji:nrierit~ of the estiniat,ioIi algorithm. Tlir CRLB t,ritc*ts approach makes intuitive s i x w sincc the, t r a w of t hr! c.ov;iriarice niiitrix is the nio;tsurf' for defining optiinality in Iialman filters [SI, antl the t1ir~)retiid co\.ariitncc. r1iittri.u for two well known Cartesiaii rst iniation algorithms. t l~ Sttrrisfielti and thc Maxiniiini 1,ikolihood rnetliocls [(j:. itre itlso t . h~ S U I I~ ii.5 tho C'RLB.A previous study on calculating optimitl paths is based on maximizing the dctermin;tiit of the Fisher inforrriation mat,rix (FIM) of t,he estirnation problem [7]. the inverse of the CRLB. That approach minimizes the area of a confidence ellipsoid around the estimates of the initial p u sitiori and initial velocity. Using area as a performance measure may favor solutions with highly eccentric confidence ellipsoids. This behavior may be troublesome in sourcr localizat,ion, since the largest ambiguity in the confidence ellipsoid often corresponds to the unknown range variablc, whilc the smaller axis often corresponds to the known bearing measurements.The performance criterion in this piaper is the tracci of the soiircv position CRLB. The tracr of the cov...