|
207 | 207 | \boldsymbol D_{\hat F\hat F}=\hat\sigma_0^2\boldsymbol Q_{\hat F\hat F} |
208 | 208 | $$ |
209 | 209 |
|
210 | | -## 附有限制条件的间接平差 |
211 | | - |
212 | | -### 模型 |
213 | | - |
214 | | -$$ |
215 | | -\begin{cases} |
216 | | -\hat{\boldsymbol L}=\boldsymbol B\hat{\boldsymbol X}+\boldsymbol d \\ |
217 | | -\boldsymbol C\hat{\boldsymbol X}+\boldsymbol C_0=\boldsymbol 0 |
218 | | -\end{cases} |
219 | | -$$ |
220 | | - |
221 | | -令 |
222 | | - |
223 | | -$$ |
224 | | -\hat{\boldsymbol X}=\boldsymbol X_0+\hat{\boldsymbol x}, |
225 | | -\quad |
226 | | -\boldsymbol l=\boldsymbol L-\boldsymbol B\boldsymbol X_0-\boldsymbol d, |
227 | | -\quad |
228 | | -\boldsymbol W_x=-(\boldsymbol C\boldsymbol X_0+\boldsymbol C_0) |
229 | | -$$ |
230 | | - |
231 | | -得 |
232 | | - |
233 | | -$$ |
234 | | -\begin{cases} |
235 | | -\boldsymbol V=\boldsymbol B\hat{\boldsymbol x}-\boldsymbol l \\ |
236 | | -\boldsymbol C\hat{\boldsymbol x}-\boldsymbol W_x=\boldsymbol 0 |
237 | | -\end{cases} |
238 | | -$$ |
239 | | - |
240 | | -### 解算 |
241 | | - |
242 | | -由最小二乘与拉格朗日法可得块法方程 |
243 | | - |
244 | | -$$ |
245 | | -\begin{bmatrix} |
246 | | -\boldsymbol B^{\rm T}\boldsymbol P\boldsymbol B & \boldsymbol C^{\rm T} \\ |
247 | | -\boldsymbol C & \boldsymbol 0 |
248 | | -\end{bmatrix} |
249 | | -\begin{bmatrix} |
250 | | -\hat{\boldsymbol x} \\ |
251 | | -\boldsymbol k |
252 | | -\end{bmatrix} |
253 | | -= |
254 | | -\begin{bmatrix} |
255 | | -\boldsymbol B^{\rm T}\boldsymbol P\boldsymbol l \\ |
256 | | -\boldsymbol W_x |
257 | | -\end{bmatrix} |
258 | | -$$ |
259 | | - |
260 | | -解出 $\hat{\boldsymbol x}$ 后仍有 |
261 | | - |
262 | | -$$ |
263 | | -\boldsymbol V=\boldsymbol B\hat{\boldsymbol x}-\boldsymbol l,\quad |
264 | | -\hat{\boldsymbol X}=\boldsymbol X_0+\hat{\boldsymbol x},\quad |
265 | | -\hat{\boldsymbol L}=\boldsymbol L+\boldsymbol V |
266 | | -$$ |
267 | | - |
268 | | -::: example |
269 | | - |
270 | | -为确定某一抛物线方程 $y^2=ax$,观测了 4 组数据,且 $x_i$ 无误差,$y_i$ 为相互独立的等精度观测值,试用间接平差求: |
271 | | - |
272 | | -1. 该抛物线方程; |
273 | | -2. 待定系数 $\hat a$ 的中误差。 |
274 | | - |
275 | | -| 点号 | $x$/cm | $y$/cm | |
276 | | -| ---- | ------ | ------ | |
277 | | -| 1 | 1 | 1.90 | |
278 | | -| 2 | 2 | 2.70 | |
279 | | -| 3 | 3 | 3.35 | |
280 | | -| 4 | 4 | 4.32 | |
281 | | - |
282 | | ---- |
283 | | - |
284 | | -依题意,有 $n=4,t=1,r=n-t=3$。 |
285 | | - |
286 | | -令 $\varGamma=\sqrt a$,则 |
287 | | - |
288 | | -$$ |
289 | | -\hat y_i=\hat\varGamma\sqrt{x_i} |
290 | | -$$ |
291 | | - |
292 | | -有 |
293 | | - |
294 | | -$$ |
295 | | -\hat{\boldsymbol L}=\boldsymbol B\hat\varGamma |
296 | | -$$ |
297 | | - |
298 | | -其中 |
299 | | - |
300 | | -$$ |
301 | | -\boldsymbol L= |
302 | | -\begin{bmatrix} |
303 | | -1.90 \\ |
304 | | -2.70 \\ |
305 | | -3.35 \\ |
306 | | -4.32 |
307 | | -\end{bmatrix}, |
308 | | -\quad |
309 | | -\boldsymbol B= |
310 | | -\begin{bmatrix} |
311 | | -1 \\ |
312 | | -\sqrt2 \\ |
313 | | -\sqrt3 \\ |
314 | | -2 |
315 | | -\end{bmatrix} |
316 | | -$$ |
317 | | - |
318 | | -取近似值 |
319 | | - |
320 | | -$$ |
321 | | -\varGamma_0=\frac14\sum\frac{y_i}{\sqrt{x_i}}=1.97583 |
322 | | -$$ |
323 | | - |
324 | | -设 |
325 | | - |
326 | | -$$ |
327 | | -\hat\varGamma=\varGamma_0+\hat\lambda |
328 | | -$$ |
329 | | - |
330 | | -因观测值等精度,故 |
331 | | - |
332 | | -$$ |
333 | | -\boldsymbol P=\boldsymbol I |
334 | | -$$ |
335 | | - |
336 | | -误差方程为 |
337 | | - |
338 | | -$$ |
339 | | -\boldsymbol V=\boldsymbol B\hat\lambda-\boldsymbol l |
340 | | -$$ |
341 | | - |
342 | | -其中 |
343 | | - |
344 | | -$$ |
345 | | -\boldsymbol l=\boldsymbol L-\boldsymbol B\varGamma_0= |
346 | | -\begin{bmatrix} |
347 | | --0.07583 \\ |
348 | | --0.09455 \\ |
349 | | --0.07224 \\ |
350 | | -0.36834 |
351 | | -\end{bmatrix} |
352 | | -$$ |
353 | | - |
354 | | -法方程为 |
355 | | - |
356 | | -$$ |
357 | | -\boldsymbol N_{bb}\hat\lambda-\boldsymbol U=0 |
358 | | -$$ |
359 | | - |
360 | | -其中 |
361 | | - |
362 | | -$$ |
363 | | -\begin{gathered} |
364 | | -\boldsymbol N_{bb}=\boldsymbol B^{\rm T}\boldsymbol P\boldsymbol B |
365 | | -=\boldsymbol B^{\rm T}\boldsymbol B=10 \\ |
366 | | -\boldsymbol U=\boldsymbol B^{\rm T}\boldsymbol P\boldsymbol l |
367 | | -=\boldsymbol B^{\rm T}\boldsymbol l=0.40245 |
368 | | -\end{gathered} |
369 | | -$$ |
370 | | - |
371 | | -故 |
372 | | - |
373 | | -$$ |
374 | | -\hat\lambda=\boldsymbol N_{bb}^{-1}\boldsymbol U |
375 | | -=\frac1{10}\times0.40245=0.04025 |
376 | | -$$ |
377 | | - |
378 | | -于是 |
379 | | - |
380 | | -$$ |
381 | | -\begin{gathered} |
382 | | -\hat a=\hat\varGamma^2=4.06458 \\ |
383 | | -\hat\varGamma=\varGamma_0+\hat\lambda=2.01608 |
384 | | -\end{gathered} |
385 | | -$$ |
386 | | - |
387 | | -又有 |
388 | | - |
389 | | -$$ |
390 | | -\boldsymbol Q_{\hat\lambda\hat\lambda}=\boldsymbol N_{bb}^{-1}=\frac1{10} |
391 | | -$$ |
392 | | - |
393 | | -改正数为 |
394 | | - |
395 | | -$$ |
396 | | -\boldsymbol V=\boldsymbol B\hat\lambda-\boldsymbol l= |
397 | | -\begin{bmatrix} |
398 | | -0.11608 \\ |
399 | | -0.15117 \\ |
400 | | -0.14195 \\ |
401 | | --0.28784 |
402 | | -\end{bmatrix} |
403 | | -$$ |
404 | | - |
405 | | -单位权方差估值为 |
406 | | - |
407 | | -$$ |
408 | | -\hat\sigma_0^2 |
409 | | -=\frac{\boldsymbol V^{\rm T}\boldsymbol P\boldsymbol V}{r} |
410 | | -=\frac{\boldsymbol V^{\rm T}\boldsymbol V}{3} |
411 | | -=0.04644 |
412 | | -$$ |
413 | | - |
414 | | -由误差传播定律, |
415 | | - |
416 | | -$$ |
417 | | -\boldsymbol Q_{\hat a\hat a} |
418 | | -=(2\hat\varGamma)^2\boldsymbol Q_{\hat\lambda\hat\lambda} |
419 | | -=1.62583 |
420 | | -$$ |
421 | | - |
422 | | -故 |
423 | | - |
424 | | -$$ |
425 | | -D_{\hat a\hat a} |
426 | | -=\hat\sigma_0^2\boldsymbol Q_{\hat a\hat a} |
427 | | -=0.07550 |
428 | | -=\sigma_{\hat a}^2 |
429 | | -$$ |
430 | | - |
431 | | -因此 |
432 | | - |
433 | | -$$ |
434 | | -\sigma_{\hat a}=\sqrt{\sigma_{\hat a}^2}=0.27478 |
435 | | -$$ |
436 | | - |
437 | | -综上,有 |
438 | | - |
439 | | -$$ |
440 | | -\hat a=4.065,\quad \sigma_{\hat a}=0.275 |
441 | | -$$ |
442 | | - |
443 | | -抛物线方程近似为 $y^2=4.065x$。 |
444 | | - |
445 | | -::: |
446 | | - |
447 | 210 | ## 应用要点 |
448 | 211 |
|
449 | 212 | - 测边网:参数取待定点坐标,观测方程为边长函数,对坐标线性化后列误差方程 |
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