Robust Shrinkage Range Estimation Algorithms Based on Hampel and Skipped Filters

<table class="figure-group"><tr class="fig-image" id="a"><td><object data="https://static-preview.hindawi.com/articles/wcmc/volume-2019/6592406/figures/6592406.fig.008a.svgz" name="6592406.fig.008a" type="image/svg+xml"></object></td></tr><tr class="fig-caption"><td><b>(a) </b>Standard deviation of LOS noise (<span class="nowrap"><svg height="9.32509pt" id="M140" style="vertical-align:-3.1815pt" version="1.1" viewbox="-0.0498162 -6.14359 11.8314 9.32509" width="11.8314pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"><g transform="matrix(.013,0,0,-0.013,0,0)"><path d="M548 455L523 469C505 448 490 439 461 439C416 439 374 447 316 447C144 447 23 310 23 161C23 47 89 -12 179 -12C312 -12 429 106 429 244C429 303 419 344 368 386L371 388C404 383 440 378 474 378C507 378 530 411 548 455ZM350 274C350 191 308 25 198 25C144 25 108 75 108 157C108 264 170 395 276 395C296 395 320 384 333 360C347 334 350 316 350 274Z"></path></g><g transform="matrix(.0091,0,0,-0.0091,6.76,3.132)"><path d="M389 0V32C297 38 291 46 291 118V635C234 613 175 595 109 583V556L161 554C203 552 207 547 207 497V118C207 46 201 38 110 32V0H389Z"></path></g></svg>):</span> <svg height="13.1484pt" id="M141" style="vertical-align:-1.442801pt" version="1.1" viewbox="-0.0498162 -11.7056 22.5957 13.1484" width="22.5957pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"><g transform="matrix(.013,0,0,-0.013,0,-1.465)"><path d="M782 731H740L476 -79H474L280 352L133 274L151 239L242 286L473 -219L782 731Z"></path></g><rect height="0.65243" width="12.5268" x="9.96925" y="-11.0034"></rect><g transform="matrix(.013,0,0,-0.013,9.969,0)"><path d="M384 0V27C293 34 287 42 287 114V635C232 613 172 594 109 583V559L157 557C201 555 205 550 205 499V114C205 42 199 34 109 27V0H384Z"></path></g><g transform="matrix(.013,0,0,-0.013,16.209,0)"><path d="M241 635C89 635 35 457 35 312C35 153 89 -12 240 -12C390 -12 443 166 443 312C443 466 390 635 241 635ZM238 602C329 602 354 454 354 312C354 172 330 22 240 22C152 22 124 173 124 313S148 602 238 602Z"></path></g></svg> m</td></tr><tr class="fig-image" id="b"><td><object data="https://static-preview.hindawi.com/articles/wcmc/volume-2019/6592406/figures/6592406.fig.008b.svgz" name="6592406.fig.008b" type="image/svg+xml"></object></td></tr><tr class="fig-caption"><td><b>(b) </b>Standard deviation of LOS noise (<span class="nowrap"><svg height="9.32509pt" id="M142" style="vertical-align:-3.1815pt" version="1.1" viewbox="-0.0498162 -6.14359 11.8314 9.32509" width="11.8314pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"><g transform="matrix(.013,0,0,-0.013,0,0)"><path d="M548 455L523 469C505 448 490 439 461 439C416 439 374 447 316 447C144 447 23 310 23 161C23 47 89 -12 179 -12C312 -12 429 106 429 244C429 303 419 344 368 386L371 388C404 383 440 378 474 378C507 378 530 411 548 455ZM350 274C350 191 308 25 198 25C144 25 108 75 108 157C108 264 170 395 276 395C296 395 320 384 333 360C347 334 350 316 350 274Z"></path></g><g transform="matrix(.0091,0,0,-0.0091,6.76,3.132)"><path d="M389 0V32C297 38 291 46 291 118V635C234 613 175 595 109 583V556L161 554C203 552 207 547 207 497V118C207 46 201 38 110 32V0H389Z"></path></g></svg>):</span> 17 m</td></tr></table>

<div>Comparison of true and approximated variances of the ML estimator as a function of distance.</div>

Wireless Communications and Mobile Computing

fig8

Figure 8

Figure 8: Robust Shrinkage Range Estimation Algorithms Based on Hampel and Skipped Filters 